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AgentEvolver: System-Wide Self-Evolution Through Task Execution

Wentao Zhang, Fuchao Yang, Yilei Zhao, Xinrun Wang, Bo An

arXiv:2610.11613v1cs.AI

TL;DR

AgentEvolver addresses how task experience can become reusable capability when revisions, evaluation, and later use must remain connected. It coordinates versioned capability changes during task execution while keeping the foundation model fixed. The team reports a higher SWE-bench Pro Public resolution rate with evolution, while six application cases document both later use and incomplete outcomes.

  • Problem

    Prior approaches make experience reusable in different ways, while the connection between heterogeneous component revisions, their evaluation, and later use during an unfinished task remains the focus of this work.

    Source: §2 · p. 3

  • Method

    AgentEvolver coordinates versioned capability changes during continuing tasks, and its case analysis reconstructs requirements, candidate versions, comparisons, retention decisions, and later consumers.

    Source: §4.2 · p. 10, §6 · p. 13

  • Results

    82.08% of tasks were resolved with evolution versus 79.07% without evolution, while six cases document later capability use alongside incomplete objectives and an unsuccessful strategy.

    Source: §4.1 · p. 9, §4.2.3 · p. 12

  • Takeaways & Limitations

    The findings motivate evaluating agents through both their deliverables and the capabilities they retain, while distinguishing local component improvement from final-task success.

    Source: §4.2.3 · p. 12, §6 · p. 13

    The selected cases do not establish platform-wide success or gains across all eight families, and independent-consumer generalization and total development cost remain open questions.

    Source: §5 · p. 12

Abstract

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An agent can complete a task without improving how it works. Turning task experience into reusable capability requires connecting the changed component to its evaluation and subsequent use. We present AgentEvolver, a system for developing capabilities during task execution while keeping the foundation model fixed. Eight entity families expose reusable operations, methods, agents, control flow, interfaces, and supporting state to revision through a common versioned lifecycle. A shared Runtime coordinates ongoing work, while persistent planning and recoverable context preserve task direction and supporting evidence. We evaluate task outcomes on SWE-bench Pro Public and examine capability changes in six application cases. The team reports an 82.08\% resolution rate with evolution, exceeding its reported baseline without evolution. The cases show retained capabilities entering later website, game, and research work, while also documenting incomplete objectives and an unsuccessful strategy. These findings distinguish improvement in a reusable component from success on the final task. AgentEvolver provides a concrete basis for studying capability accumulation through execution; independent-task transfer and total development cost remain open questions.

2 RELATED WORK

Prior work makes experience reusable through feedback, executable skills, revised agent programs, or model learning; AgentEvolver focuses on revising heterogeneous software components during an unfinished task, linking execution, version identity, and retention evidence. The related work distinguishes adaptation targets and highlights coordination, context recovery, and evaluation conditions.

2.1 FEEDBACK AND REUSABLE CAPABILITIES

  • ReAct, Reflexion, and Voyager retain experience in different forms, while AgentEvolver distinguishes task records, operating methods, and executable operations by their interfaces and evaluation needs.Other approaches adapt tool-use behavior or model parameters, whereas AgentEvolver holds the foundation model fixed and changes the surrounding capability system.Source: §2.1 · p. 3

2.2 AGENT DESIGN AND RUNTIME SELF-MODIFICATION

  • AgentEvolver emphasizes coordinating heterogeneous software revisions during continuing tasks, with the acting agent proposing changes and the framework maintaining component identities and evidence.The cited work spans pipeline optimization, agent-program search, scaffold modification, recursive revision mechanisms, and task-generation approaches; the paper does not establish controlled superiority over Live-SWE-agent or recursive improvement.Source: §2.2 · pp. 3–4

2.3 COORDINATION, CONTEXT, AND EVALUATION

  • Runtime links delegated processes and operations to owners, resources, and lifecycle states, while Plan, working context, and archived observations support recovery of task direction and capability evidence.The paper notes that ablations are needed to quantify individual coordination mechanisms.Source: §2.3 · p. 4

2.4 TASK EVALUATION AND ADAPTIVE SELECTION

  • Task identity, feedback, resource limits, and grading conditions govern which benchmark comparisons are supported, and repeated selection on observed feedback can bias evaluation.The analysis separates development comparisons, later use, and independent held-out assessment.Source: §2.4 · p. 4

3 AGENTEVOLVER

AgentEvolver models task execution and capability development together while keeping the foundation model fixed. Its design combines eight versioned capability families, Runtime coordination, persistent planning and context, and an evidence-based lifecycle for proposing, evaluating, retaining, and using changes.

3.1 PROBLEM SETTING AND DESIGN REQUIREMENTS

  • Execution state separates the deliverable, archived and active component versions, runtime processes and ownership, planning records, and remaining budget.Ordinary task actions and evolution actions share Runtime and budget accounting, but final deliverable acceptance and capability evidence remain distinct.Source: §3.1 · p. 4

3.2 EIGHT EVOLUTION SURFACES AND THE UNIT OF CHANGE

  • Eight versioned families cover callable capabilities, Environment, and Memory, with change surfaces chosen to match consumer needs rather than treating every component as a stateless function.The paper distinguishes reusable component revisions from ordinary activity such as dispatching another worker, updating Plan content, or writing a Memory record.Source: §3.2 · pp. 5–6

3.3 RUNTIME: COORDINATING WORK WHILE CAPABILITIES CHANGE

  • Runtime coordinates persistent agent processes and bounded component invocations, recording ownership, parent calls, component identity, status, and resource claims.Interruption rules keep child work and in-flight operations visible; shared resource accounting includes construction, failed attempts, evaluation, and later consumption.Source: §3.3 · p. 6

3.4 PLAN AND CONTEXT: PRESERVING DIRECTION AND EVIDENCE

  • Plan keeps a compact current index linked to detailed objectives and decisions, while Context retains recent interactions and archives compacted history for recovery.Trace records requests, actions, and observations so retention decisions can be reconstructed alongside version history.Source: §3.4 · pp. 6–7

3.5 FROM AN OBSERVED GAP TO A RETAINED CAPABILITY

  • The agent proposes a versioned candidate and domain-specific comparison, while the framework checks admission, execution provenance, evidence consistency, and retention state.Structural admission is separate from functional evaluation; passing evidence must reference executed calls, while the submitting agent supplies the substantive judgment.Source: §3.5 · pp. 7–8
  • A retained capability counts as used only when a later successful consumer is tied to its version; applicability conditions and final deliverable acceptance remain separate.The LUMEN chain illustrates interdependent Connector, Agent, and Skill revisions, while independent-task transfer requires evaluation with a frozen capability library.Source: §3.5 · p. 8

4 EMPIRICAL STUDIES

The empirical studies report higher repository-repair totals with evolution enabled and trace how retained capability changes enter later application work. The cases also show that local capability improvements do not guarantee completion or success on the final objective.

4.1 SWE-BENCH PRO PUBLIC: TASK-LEVEL COMPARISON

  • The inspected conditions share a model route, task interface, planning support, and resource limits; separate-machine totals lack raw per-task results and verified realized settings.The evolution-enabled condition additionally mounts the adoption Tool and self-evolving Skill; Table 3 describes inspected defaults, not a verified execution manifest.Source: §4.1 · p. 9, Table 3 · p. 9
  • External benchmark rows use different models, harnesses, budgets, and grading conditions; aggregate totals also do not establish paired task changes or attribute gains to a subsystem.The external snapshot is contextual rather than a controlled product ranking.Source: §4.1 · p. 9
  • 82.08% (600/731) of tasks were resolved with evolution, versus 79.07% (578/731) without it—a 3.01-percentage-point gain and 22 net additional resolved tasks.Figure 4 presents this team-reported internal comparison.Source: §4.1 · p. 9, Figure 4 · p. 10

4.2 SIX APPLICATION CASES: PRODUCTS AND THE CAPABILITIES BEHIND THEM

  • The six purposively selected historical cases reconstruct capability-change episodes, comparing local evaluation and later use separately from final task outcomes.The collection includes partial and unsuccessful outcomes but is not exhaustive.Source: §4.2 · pp. 9–10

4.2.1 FOUR WEBSITES AS CONTINUING DESIGN WORK

  • Commonspace traces four affected objects among nine after a source revision; LUMEN’s Connector, specialist, and review Skill enter later work, while ARKBOUND tests bounded acquisition and paired play.ORBITAL rejects a wrong-date source fixture and retrieves an identified Mars packet, but its required review Skill lacks adoption and use evidence, leaving the objective incomplete.Source: §4.2.1 · pp. 10–12

4.2.2 GAME DEVELOPMENT AND RESEARCH INFRASTRUCTURE

  • The Godot font-realization Skill reaches a later label consumer, a brightness Tool reduces median latency by 30.08% on a real-frame fixture, and Signal Foundry replays a strategy that fails its comparative criterion.The brightness measurement is a local operation comparison; the retained Skill’s use is distinct from delivery of the unfinished game.Source: §4.2.2 · p. 12

4.2.3 CROSS-CASE FINDINGS AND OPEN QUESTIONS

  • Across cases, semantic failures motivate revisions, and later consumers use retained changes; ORBITAL, Godot, and Signal Foundry nevertheless retain incomplete or unsuccessful final outcomes.The cases support analysis of specific capability changes and subsequent use, not a platform-wide success rate.Source: §4.2.3 · p. 12
  • Whether frozen capabilities transfer to independent tasks and whether local operation savings recover development cost remain open questions.The cases also leave open how an unconstrained agent selects a component family to revise.Source: §4.2.3 · p. 12

5 DISCUSSION AND LIMITATIONS

The discussion limits the strength of the evaluation and identifies coverage, attribution, reproducibility, and cost questions that remain open.

Evaluation quality

  • Versioned observations do not validate evaluator fixtures, baselines, or judgments, and repeated selection can overfit development feedback.Stronger conclusions require independent acceptance tests, preserved failed attempts, and a frozen candidate before final evaluation.Source: §5 · p. 12

Coverage, attribution, and cost

  • The six selected cases do not establish platform-wide success rates or gains across all eight families, and the team-reported SWE comparison lacks paired outcomes for attribution and uncertainty estimates.Website checks also leave user satisfaction and learning outcomes unmeasured; generalization and cost effectiveness require independent consumers tested under matched budgets while accounting for regressions, abandoned candidates, and total development cost.Source: §5 · p. 12

Execution and reproducibility

  • Declared access, lossy summaries, interrupted operations, provisional activation, and changing dependencies complicate execution and reproducibility.Reproduction requires inputs, dependency and environment records, and execution history alongside source bytes; mechanism-specific ablations and recovery tests should assess effects on final task acceptance.Source: §5 · pp. 12–13

6 CONCLUSION

The conclusion frames AgentEvolver as linking task execution to reusable capability development, with safeguards and limits for recoverable context, Workflow composition, and session-scoped notes and retrieval. It distinguishes architectural support from capability changes demonstrated in selected cases and argues for evaluating both task outcomes and retained capabilities, while leaving independent-task transfer and development cost open.

6 CONCLUSION

  • AgentEvolver treats deliverable quality and reusable capability improvement as distinct outcomes, and its conclusion calls for evaluating both while testing transfer and development cost.A completed task does not establish that a component improved, and retaining a useful component does not establish task completion.Source: §6 · p. 13

A CORE SYSTEM CAPABILITIES; A.1 TWO COUPLED FORMS OF PROGRESS

  • The system separates the deliverable, archived versions, and active capabilities, and develops changes selectively when a concrete limitation suggests a reusable operation and consumer.The appendix frames task-driven capability development as complementary to execution, planning, and context mechanisms; task-specific criteria determine what counts as improvement.Source: §A.1 · pp. 15–16, A CORE SYSTEM CAPABILITIES · p. 15

A.2 EIGHT FAMILIES, DISTINCT OPERATIONAL ROLES

  • Eight component families have distinct operational roles; separating Environment state and Memory content from implementation changes clarifies what the reusable system actually evolved.The family boundary helps match interventions to needs: a narrow operation may become a Tool, while a multi-step procedure may remain a Skill using existing Tools; some cases combine families.Source: §A.2 · pp. 16–17

A.3 VERSIONED DEVELOPMENT AND RETENTION

  • Versioned identity and evaluation records connect a candidate to its implementation and observations, but successful admission alone does not establish usefulness or task-level success.Later use of a retained version in another step of the same project is task-local evidence; independent-task transfer requires a separate evaluation with an unexposed consumer.Source: §A.3 · p. 17

A.4 RUNTIME OWNERSHIP AND PROCESS LIFETIMES

  • Runtime assigns ownership and lifecycles to Agent processes separately from bounded component calls, enabling coordinated work while distinguishing a waiting process from a finished one.In the motivating pattern, product work can proceed while a specialist evaluates a needed interface; the coordinator consumes it after the dependency is satisfied and checks the product.Source: §A.4 · pp. 17–18

A.5 RESOURCE COORDINATION AND BOUNDED DELEGATION; A.6 BUDGETING ACROSS THE COMPLETE DEVELOPMENT PROCESS

  • Resource claims and bounded delegation coordinate declared work, but do not guarantee isolation from undeclared or external effects; fair comparisons must account for the full development process and realized resource use.The shared budget includes candidate construction, evaluation, failed attempts, and later consumption; the coding aggregates lack full paired accounting, so they do not establish cost efficiency.Source: §A.6 · pp. 19–20, §A.5 · p. 19

A.7 PLAN: PERSISTENT DIRECTION FOR CHANGING WORK

  • The Plan preserves the objective, unresolved dependencies, and evidence references, while separating intended progress from runtime state and acceptance evidence.When evolution policy is enabled, opportunities link a task limitation to a reusable method, intended consumer, expected benefit, and comparison or reuse experiment; the plan itself does not certify historical claims.Source: §A.7 · pp. 20–21

A.8 CONTEXT ASSEMBLY AND RECOVERABLE COMPRESSION

  • Context assembly balances request size and recoverability by retaining stable task anchors, recent complete exchanges, and references to archived material.Compression occurs at closed interaction boundaries, preserving recent calls and results together; the approach retains explicit failure and recovery behavior rather than treating a longer context as sufficient for reliable retrieval.Source: §A.8 · p. 21
  • A candidate checkpoint replaces history only when measuring the complete request shows a reduction; persistent-thread archives retain a route to prior evidence, unlike unbound calls.Compression can still omit qualifications, and request savings do not establish semantic completeness; evaluation should measure both resource behavior and continuation quality.Source: §A.8 · pp. 22–23

A.9 WORKFLOW AND PROGRAMMATIC COMPOSITION

  • Workflows provide reusable, checkpointed control flow, while Code Mode composes operations in a fresh Python child; its process boundary is not an operating-system security sandbox.Code Mode’s efficiency gains are unmeasured; establishing them requires matched operations, equivalent outputs, and complete request accounting.Source: §A.9 · pp. 23–24

A.10 MEMORY, CONVERSATION CONTINUITY, AND HISTORICAL RETRIEVAL

  • Session-scoped notes do not establish automatic knowledge transfer across projects, and the selected cases do not demonstrate a controlled Memory improvement.Notes are fallible references, so useful retention should preserve an observation’s origin and scope; the empirical cases focus on Tool, Skill, Agent, Connector, and Environment changes.Source: §A.10 · p. 25

A.11 TRACE, RECOVERY, AND EVIDENCE-PRESERVING VIEWS

Trace, recovery, and evidence-preserving views connect execution events to evaluations, decisions, and later consumers while keeping task state and uncertainty visible. The section also describes how the application cases reconstruct those connections and where the evidence remains limited.

A.11 TRACE, RECOVERY, AND EVIDENCE-PRESERVING VIEWS

  • Trace links effective requests, actions, component results, and lifecycle events to version-specific observations, while derived views do not independently validate authored judgments.Request snapshots retain the route and settings actually attempted; tool records preserve version, outcome, timing, and call relationships.Source: §A.11 · p. 25, Figure 11 · p. 26
  • Durability depends on the selected profile, projections persist output before advancing, and compaction preserves original events while changing the active conversational view.Recovery distinguishes restored dialogue, queued assignments, and browser state from arbitrary processes or confirmed external actions; possibly executed operations require reconciliation.Source: §A.11 · pp. 26–27
  • Requests and trajectories may contain sensitive task data, so exporting or sharing evidence requires selecting records and preserving the appropriate data boundary.Structured records avoid dedicated credential fields but cannot prevent sensitive information from appearing in messages or observations.Source: §A.11 · p. 27

A.12 WHAT THE CORE MECHANISMS ENABLE, AND WHAT REMAINS TO MEASURE

  • Component identities, Runtime, Plan, context management, composition, Memory, and Trace connect capability development to the continuing task, but most mechanisms lack isolated evaluation.Targeted controls are still needed for recovery reliability, compression quality, parallel efficiency, and cross-task library value.Source: §A.12 · p. 27

B.1 STUDY DESIGN AND VISUAL EVIDENCE

  • The six cases are historical development sequences reconstructed from intent through consumer and product outcome, not random samples or independent replications.Selected product views provide context; component observations support quantitative and adoption claims.Source: §B.1 · p. 27, Table 6 · p. 28, Figure 12 · p. 28

B.2.1 APPLICATION INTENT AND OBSERVED GAP

  • In Commonspace, a semantic revision method isolated G01's change from 5 to 2 despite metadata changes, but identifying the changed row did not reveal its downstream dependencies.The case treats two sessions as stages in one product sequence.Source: §B.2.1 · pp. 28–29, §B.2.4 · p. 29

B.2.2 RETAINED CAPABILITY AND ACTUAL CONSUMER

  • The retained reference_impact_trace operation identified four review candidates among nine inspected objects, and its recorded consumer connected the changed source to affected project actions.Four of nine is a count from one graph, not a precision or recall score; the operation's generalization and correctness remain unestablished.Source: §B.2.2 · p. 29, §B.2.3 · p. 29, §B.2.4 · p. 29

B.3.1 AN INTERACTIVE MUSEUM WITH REVISABLE ROUTES

  • LUMEN's task prescribed Connector, Agent, and Skill evolution to support revisable museum inquiries, so the case examines their development and use rather than independent discovery of that design.The task required those three families, and the case's historical sessions developed source, design, and review capabilities.Source: §B.3.1 · p. 30

B.3.2 SOURCE, AUTHORING, AND REVIEW RESPONSIBILITIES

LUMEN's Connector, specialist Agent, and review Skill handle distinct source, authoring, and historical-evidence responsibilities. Their later use forms a task-local chain, while the case leaves independent scientific and visitor evaluation open.

B.3.2 SOURCE, AUTHORING, AND REVIEW RESPONSIBILITIES

  • The Connector creates bounded source packets with identity, retrieval, content-status, and integrity information, preserving metadata-only limits rather than implying full-text inspection.A later source resolution supplied the packet imported into the product; request timings do not establish faster retrieval.Source: §B.3.2 · p. 30
  • The specialist Agent structures inquiries under source and interaction constraints, and the retained version was linked to an integrated route rather than only an isolated review response.Recorded routes included five steps totaling 360 seconds and a separate five-step, 300-second fixture; a later R4 revision changed a 90-second original-colour condition to a 150-second swapped-colour condition.Source: §B.3.2 · p. 30
  • On a recorded defect fixture, the review Skill found five issues despite ordinary structural validation passing, and a later consumer executed the retained method on an actual route revision.The five-issue count belongs to that fixture; other checks kept manual-review branches explicit.Source: §B.3.2 · p. 31

B.3.3 A CONNECTED CHAIN, WITH BOUNDED CONCLUSIONS

  • The post-adoption chain connected a qualified source packet to specialist authoring, retained-Skill review, and browser observations while preserving earlier notebook entries with review notices.The case supports a versioned, task-local chain, not independent astronomy or scientific validation; review judgments were builder-authored.Source: §B.3.3 · p. 31

B.3.4 DESIGNING A MUSEUM THAT CAN REVISE ITS OWN INQUIRIES

  • Separating source qualification, interaction design, and historical review helps distinguish errors that could otherwise produce similar-looking problems in the final page.Retaining both the original and changed R4 conditions lets later visitors or reviewers relate observations to the design under which they were recorded.Source: §B.3.4 · pp. 31–32

B.3.5 READING THE VISUAL SEQUENCE

  • Selected product views show where component responsibilities appear, but do not constitute additional capability trials or establish platform accuracy.The figure presents twelve selected views; the ARKBOUND Connector's separate bounded-acquisition evidence reports 666,655 bytes within a 700,000-byte allowance, not visual quality or faster rendering.Source: Figure 13 · p. 31, §B.3.5 · p. 32, Table 8 · p. 32

B.4.2 A FAILED CANDIDATE AND A RETAINED REVIEW METHOD

The ARKBOUND case preserves both failed development and later product checks: a candidate was rolled back, while review and acceptance records document comparisons and integration under stated conditions.

B.4.2 A FAILED CANDIDATE AND A RETAINED REVIEW METHOD

  • The 1.0.3 Agent candidate was rolled back because the intended prompt update was not realized in the running definition, illustrating the need to reconcile source bytes, loaded behavior, and version identity.The retained paired-play review Skill controls starting state, but multiple conditions changed in the revised voyage, making it a paired product check rather than a single-factor experiment.Source: §B.4.2 · p. 33

B.4.3 INTEGRATED PRODUCT AND EVIDENCE BOUNDARIES

  • Final acceptance records describe connected voyage loops, route reconstruction, and saved-state recovery, but builder self-play leaves paths unverified and interaction weaknesses unresolved.An earlier Agent-use receipt still marked browser integration pending; later acceptance records provide additional integration evidence.Source: §B.4.3 · p. 33

B.4.5 READING THE VISUAL SEQUENCE

  • The figure's selected views connect resource acquisition, reusable review, and the voyage, while the paired review—not visual sequence alone—supports comparison under a documented starting state.The twelve views are a reading guide, not additional trials.Source: §B.4.4 · p. 34, §B.4.5 · p. 34, Table 9 · p. 34

B.4.4 PRESERVING COMPARABILITY WHILE THE VOYAGE CHANGES

  • Restoring the same prelaunch export reduces ambiguity from stateful interaction, but revisions that change several authored conditions remain matched-start product comparisons, not single-variable experiments.The case recommends identifying changed conditions in the paired record.Source: §B.4.4 · p. 34

B.5.1 APPLICATION INTENT AND SEMANTIC VALIDATION

ORBITAL examines semantic consistency between source data and an astronomy interface. Its retained Connector and specialist Agent support a limited downstream chain, but the required review-Skill adoption remained incomplete.

B.5.1 APPLICATION INTENT AND SEMANTIC VALIDATION

  • The ORBITAL Connector rejected a date-misaligned response despite an equal record count, then supplied a new Mars packet validated as four daily states with units, frame, and time standard retained.These are source-contract observations, not proof that the full astronomical model is physically faithful.Source: §B.5.1 · pp. 34–35, Figure 15 · p. 35

B.5.2 SPECIALIST BEHAVIOR AND INCOMPLETE ADOPTION

  • The retained specialist Agent distinguished corrections to units, frames, assumptions, and display choices, and its output entered a residual notebook while preserving original Earth material.The required review Skill lacked adoption and use evidence, leaving the task readiness record false and the objective incomplete.Source: §B.5.2 · p. 35

B.5.3 WHAT THE CASE ESTABLISHES

  • The case establishes only a limited mismatch-to-interface chain; independent astronomy validation would require externally checked fixtures, explicit frame transformations, and a review-method consumer.Data correctness, explanatory quality, and visual presentation remain separate outcomes.Source: §B.5.3 · p. 35

B.5.4 SEPARATING DATA REPAIR FROM VISUAL PLAUSIBILITY

The case distinguishes semantic source repair from visually plausible output, while documenting an evolution objective that remained incomplete. The visual sequence connects development views with later product interaction but is not a controlled visual experiment.

B.5.4 SEPARATING DATA REPAIR FROM VISUAL PLAUSIBILITY

  • The source response had the expected fields and count but dates outside the requested interval, so the revised contract checks field meaning before visualization.A plausible scene cannot establish that the source packet matches the request.Source: §B.5.4 · pp. 35–36
  • Validity spans source identity, units and time standard, coordinates, model assumptions, and presentation; correcting one level does not validate the others.The displayed scene cannot independently validate the ephemeris or the physical adequacy of its model.Source: §B.5.4 · p. 36
  • The absent adopted review Skill left the requested three-family evolution objective incomplete, despite a retained component and consumer in the historical sequence.The account preserves the partial outcome rather than treating it as complete.Source: §B.5.4 · p. 36

B.5.5 READING THE VISUAL SEQUENCE

  • The visual strip combines scene-development views with source and notebook interfaces; the ring revision is visual evidence, while rejecting a date-misaligned packet requires request-response evidence.Reading both evidence types explains local improvements without establishing completion of the full objective.Source: §B.5.5 · p. 36

B.6.1 A CONNECTED DEVELOPMENT SEQUENCE

  • Across three connected sessions, the work develops a frame-luminance Tool, investigates fonts, and retains a font-realization Skill for a later consumer.Repeatable measurements address realized engine behavior, while product changes remain specific to the scene.Source: §B.6.1 · p. 36

B.6.2 A BOUNDED NUMERICAL TOOL COMPARISON

The Godot case reports lower Tool execution times on a real frame and a separate synthetic workload, with equal returned metrics. A retained font procedure is later used to check engine realization.

B.6.2 A BOUNDED NUMERICAL TOOL COMPARISON

  • 30.08% median reduction: frame_luminance_fast version 1.0.0 ran on the same real frame with equal returned metrics, based on three observations per implementation.Figure 17 shows every recorded timing and the medians; its real-frame and synthetic-band axes are separate.Source: §B.6.2 · p. 36, Figure 17 · p. 37
  • 90.55% median reduction: the separate synthetic-band fixture recorded baseline timings of 310.12, 333.97, and 341.77 ms and candidate timings of 28.03, 31.57, and 32.09 ms.This result is reported separately because it concerns a different workload.Source: §B.6.2 · p. 37
  • Both implementations reject transparent input requiring a composited screenshot, corrupt non-PNG input, and empty or out-of-bounds regions.Output equality and rejection cases provide behavioral context for the timings.Source: §B.6.2 · p. 38
  • After adoption, the Tool measured a newly rendered frame during a later lighting review, where the recorded region had no clipping.The reviewer observed improved separation after lighting changes; this later call does not expand the three-call timing sample or establish general speedup.Source: §B.6.2 · p. 38

B.6.3 FROM FONT METADATA TO REALIZED FONT BEHAVIOR

  • The retained font Skill uses a native engine probe to identify a working numeric axis key and inspect realized text; a later Label3D consumer requesting weight 650 showed mixed-script width changing from 345 to 367.The width change indicates a different font realization, not a readability score; the full-delivery objectives remained incomplete.Source: §B.6.3 · p. 38

B.6.4 TWO IMPROVEMENTS WITH DIFFERENT OUTCOME MEASURES

The two improvements use different outcome measures: a bounded luminance diagnostic timing comparison and a font-realization check. Product-sequence views connect development and later interaction but are not a controlled visual experiment.

B.6.4 TWO IMPROVEMENTS WITH DIFFERENT OUTCOME MEASURES

  • The two retained capabilities address distinct questions: brightness analysis provides numerical observations, while font realization checks the resource used by the engine.The product views do not constitute a controlled visual experiment.Source: §B.6.4 · p. 38
  • 30.08% median reduction on one rendered input: the real-frame Tool comparison used three observations per implementation and matched returned metrics.The separate synthetic workload has a different relative reduction; neither comparison measures game-frame rendering speed or uncertainty across arbitrary images or machines.Source: §B.6.4 · p. 38
  • The later world-space label used the retained font procedure at a different weight and context; its width change and native screenshot show engine realization, not reading speed or user preference.Testing unseen fonts and contexts or evaluating user responses would require separate studies.Source: §B.6.4 · p. 38

B.6.5 READING THE VISUAL SEQUENCE

  • The sequence orders historical development images before later product-interaction views, but those play images do not share the Tool comparison’s controlled fixture.Font realization also depends on the native probe and its resource measurements.Source: §B.6.5 · p. 38

B.7.1 RESEARCH AS AN EVOLVING APPLICATION

Signal Foundry examines reusable research infrastructure alongside strategy evaluation, keeping its main run distinct from a separate failed held-out example. Retained connectors and environments support qualified data acquisition and replay of a frozen binding.

B.7.1 RESEARCH AS AN EVOLVING APPLICATION

  • The workflow acquires data, defines factors, combines strategy mechanisms, evaluates candidates, and freezes an artifact; its infrastructure case and failed held-out example are separate sessions, not replications.Reusable outputs include data qualification and stateful research environments alongside strategies that survive evaluation.Source: §B.7.1 · pp. 38–39
  • The main research run retained public_equity_connector 1.0.0, factor_lab 1.0.3, and strategy_lab 1.0.3; acquisition checked 1,838 exact trading sessions for structural properties.Structural qualification does not make a public adjusted-price proxy equivalent to an executable trading feed.Source: §B.7.1 · p. 39

B.7.2 FROZEN BINDINGS AND REPLAY

  • The two retained Environments replayed the selected three-factor S010@5 binding, with prefix parity matching feature columns, fitted records, strategy specification, and portfolio-related outputs.This supports reproducibility of a specified binding, not a newly discovered candidate or an independent selection opportunity.Source: §B.7.2 · p. 40
  • The main run contains 77 evaluated factor definitions, 20 strategy mechanisms, 40 formal strategy versions, and 26 diagnostic controls; these counts do not establish predictive quality or successful trades.Search-efficiency evaluation would require total candidate-generation and preparation costs plus comparative baselines under equivalent resources.Source: §B.7.2 · p. 40

B.7.3 TASK OUTCOME AND ADAPTIVE EVALUATION

The section separates task and infrastructure outcomes from strategy quality, showing that capability development can preserve reproducible artifacts without meeting a strategy’s acceptance criterion. It also distinguishes recorded component changes, evaluation, later use, and final task success.

B.7.3 TASK OUTCOME AND ADAPTIVE EVALUATION

  • The selected S010@5 artifact’s approximately +29.95% net proxy return accompanies approximately −0.00446 benchmark-relative utility, so it lacks the required comparative advantage.A separate held-out session returned −15.71% versus +47.72% for an annually reset buy-and-hold benchmark and failed five of seven predeclared criteria.Source: §B.7.3 · p. 40

B.7.4 RESEARCH QUALITY AND STRATEGY QUALITY ARE SEPARATE OUTCOMES

  • The 77 factor definitions, 20 mechanisms, and 40 strategy versions may share observations; the frozen utility criterion, not search volume, determines the selected strategy’s outcome.The frozen three-factor binding provides a replay target across feature definitions, fitted records, strategy specification, and portfolio outputs.Source: §B.7.4 · p. 40

B.7.5 READING THE VISUAL SEQUENCE

  • The saved-report strip is a reading sequence, not a time series of model decisions; interpret its final plots using their original run identities and evaluation boundaries.The selected interface observations are not additional component-evaluation trials.Source: §B.7.4 · p. 40, §B.7.5 · p. 41, Table 12 · p. 41

C.1 WHAT EACH EVENT ESTABLISHES

  • Admission, evaluation, retention, and verified later use establish different things; a Skill load alone does not show its method was applied.A later invocation in the same project establishes use under that project’s conditions, while an independently held-out consumer addresses stronger transfer.Source: §C.1 · p. 41

C.2 SWE-BENCH PRO COMPARISON

  • 82.0793% with evolution versus 79.0698% without it; the aggregate difference is 3.0096 percentage points, but task-level pairing cannot be inferred from the totals.Equal denominators do not establish identical task lists, and the totals do not recover a paired significance analysis.Source: §C.2 · p. 42

C.3 FURTHER EXPERIMENTS, EXPLICITLY NOT YET RUN

  • A valid evolution ablation would hold task identities, model route, initial capabilities, feedback, and grading fixed while reporting realized cost; no ablation outcomes are supplied.The reported 600/731 and 578/731 totals exclude interrupted local batches.Source: §C.3 · p. 42, §C.2 · p. 42

C.4 MECHANISM-SPECIFIC EVALUATION DESIGNS

  • Proposed mechanism-specific studies isolate persistent planning, context retrieval, Runtime coordination, and Memory retrieval behavior rather than infer their effects from a whole-system score.The plans specify matched conditions and task outcomes; the Runtime design separates deterministic contract checks from model-dependent performance.Source: §C.4 · pp. 42–43

C.5 VISUAL AND QUANTITATIVE EVIDENCE

  • Across cases, task rates, graph objects, fixture issues, bytes, invocation time, and research outcomes have distinct units and should not become one generic improvement percentage.Negative and incomplete outcomes are retained because excluding them would overstate the connection between capability activity and task success.Source: §C.5 · p. 43

C.6 IMPLEMENTATION AND ARTIFACT PROVENANCE

The provenance and reproduction account ties claims to inspected implementation versions, source records, and explicit study conditions. It also cautions that local per-use savings do not establish total development cost or a break-even point.

C.6 IMPLEMENTATION AND ARTIFACT PROVENANCE

  • The system account was checked against the implementation available on 30 September 2026, while historical runs retain their own versions and execution records.Artifact hashes establish which bytes were inspected, not whether every artifact claim is correct; the review did not freshly execute all historical tasks or independently regrade external coding results.Source: §C.6 · p. 43

C.7 REPRODUCTION PROCEDURE AND REQUIRED RECORDS

  • Reproduction records should identify the unit, inputs, initial capabilities, candidate attempts, frozen retained version, and separate component and task-acceptance criteria.A changed provider, model, or environment defines a changed-condition study; matching source bytes or displayed scores alone does not establish equivalent behavior or task membership.Source: §C.7 · p. 44, Table 13 · p. 44

C.8 AMORTIZED COST OF RETAINED CAPABILITIES

  • Positive amortized savings require lower per-use cost and enough comparable later uses to recover development cost, but the available evidence does not establish a break-even point.The report lacks complete development cost and future usage distribution; maintenance, changed workloads, and regressions can also alter the comparison.Source: §C.8 · p. 44
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