Source profileQuality 94/100

anthony-chaudhary/fak/.claude/skills/field-borrow/SKILL.md

field-borrow

High-priority default "inspired by" workflow. Invoke proactively whenever an external product, repository, paper, standard, benchmark, release, issue, PR, roadmap, design discussion, or field practice could improve fak—not only on explicit borrow requests. Mine code, tests, docs, history, releases, open/closed issues, PRs, discussions, roadmaps, and provenance; date observations and source events; directly port/adapt when exact-source licensing permits; explore the spirit of promising proposed o

Source repository stars
32
Declared platforms
0
Static risk flags
0
Last source update
2026-08-25
Source checked
2026-08-25

Decision brief

What it does: where it fits

High-priority default "inspired by" workflow. Invoke proactively whenever an external product, repository, paper, standard, benchmark, release, issue, PR, roadmap, design discussion, or field practice could improve fak—not only on explicit borrow requests.

Best for

    Not for

    • Tasks that require unconfirmed production actions or broad system permissions.
    • Environments where the pinned source and install steps cannot be inspected.

    Compatibility matrix

    Platform support, with evidence labels

    PlatformStatusEvidenceWhat to check
    CodexNot declaredNo explicit evidencePortability before use
    Claude CodeNot declaredNo explicit evidencePortability before use
    CursorNot declaredNo explicit evidencePortability before use
    Gemini CLINot declaredNo explicit evidencePortability before use
    Open the compatibility checker

    Installation

    Inspect first. Install second.

    The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

    Source-detected install commandSource
    npx skills add https://github.com/anthony-chaudhary/fak --skill ".claude/skills/field-borrow"
    Safe inspection promptEditorial

    Inspect the Agent Skill "field-borrow" from https://github.com/anthony-chaudhary/fak/blob/9646744c1510476dcd1104bbdafce9ba39c68f65/.claude/skills/field-borrow/SKILL.md at commit 9646744c1510476dcd1104bbdafce9ba39c68f65. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

    Workflow

    What the source asks the agent to do

    1. 01

      High-priority inspired-by default

      This is the repository's high-priority default "inspired by" workflow. Invoke it proactively whenever a named product, repository, paper, standard, benchmark, release, issue, PR, roadmap, design discussion, or field practice could improve fak. Do not wait for an explicit researc…

      Priority: consider external prior art early, not as optional cleanup after designing.Licensed reuse: copy or adapt directly when exact-source licensing and technical fit permit;Exhaustiveness: all relevant source classes were checked or explicitly marked unavailable.
    2. 02

      Exhaustive, dated source ledger

      For a repository-shaped source inspect canonical docs/design/API examples; code, tests, fixtures, and configuration at a pinned revision; releases/tags/changelog and relevant history/blame; open and closed issues; merged, closed, and open PRs plus review discussion; discussions,…

      observedat: full ISO date/time for the research observation;sourceeventat: commit, merge, release, publication, or update date;source state: released/shipped, merged-unreleased, proposed/open, rejected/closed,
    3. 03

      License disposition: copy when allowed

      Read the license at the exact studied revision and check per-file/NOTICE/provenance boundaries. Classify every candidate before implementation:

      DIRECT-PORT: copying/modification is permitted and obligations fit. Prefer copying theADAPT: reuse is permitted but fak interfaces, dependencies, or constraints require materialINSPIRE-ONLY: terms are absent, unclear, incompatible, proprietary, or behavior-only. Build
    4. 04

      Expansive candidate extraction

      Extract all of these before ranking:

      direct mechanisms: algorithms, schemas, tests, UX, operations, and documentation;negative knowledge: reverts, rejected proposals, recurring issue failures, regressions, reviews;emerging direction: open PRs, issues, RFCs, roadmaps, TODOs, and design sketches, marked proposed;
    5. 05

      Bounded-superset portfolio rule

      The target is not "copy the winner" and not "accumulate every feature." It is a bounded capability superset: within fak's declared scope and support budget, users should be able to trust that fak carries the strongest reasonable industry default and preserves materially useful a…

      Default frontier — where fak's common-case default should lead or change.Coverage frontier — useful supported cohorts still absent even though the default mayThe target is not "copy the winner" and not "accumulate every feature." It is a bounded capability superset: within fak's declared scope and support budget, users should be able to trust that fak carries the strongest r…

    Permission review

    Static risk signals and limitations

    No configured static risk pattern was detected

    This is not proof of safety. Runtime behavior, indirect dependencies, and hidden external systems are outside the static scan.

    Evidence record

    Why each signal appears

    EvidenceSourceComputedTestedEditorial
    SignalValueEvidence typeMeaning
    Quality score94/100ComputedDocumentation, specificity, maintenance, and trust rules
    Repository stars32SourceRepository attention, not individual Skill quality
    Compatibility0 platformsSourceDeclared in the catalog source record
    Usage guideautomated source guideEditorialGenerated or reviewed according to the visible evidence level

    Pinned source

    Provenance and original SKILL.md

    Repository
    anthony-chaudhary/fak
    Skill path
    .claude/skills/field-borrow/SKILL.md
    Commit
    9646744c1510476dcd1104bbdafce9ba39c68f65
    License
    Apache-2.0
    Collected
    2026-08-25
    Default branch
    main
    View the original SKILL.md

    field-borrow — borrow from the field, but witness the gap against yourself first

    High-priority inspired-by default

    This is the repository's high-priority default "inspired by" workflow. Invoke it proactively whenever a named product, repository, paper, standard, benchmark, release, issue, PR, roadmap, design discussion, or field practice could improve fak. Do not wait for an explicit research or borrowing request: run it before bespoke design when credible prior art may change the choice. External evidence does not override user scope, security, legal obligations, or coherent shipping.

    Six laws govern every pass:

    1. Priority: consider external prior art early, not as optional cleanup after designing.
    2. Licensed reuse: copy or adapt directly when exact-source licensing and technical fit permit; fresh reimplementation is not inherently better.
    3. Exhaustiveness: all relevant source classes were checked or explicitly marked unavailable.
    4. Dating: every observation carries event time, observation time, source state, and refresh cue.
    5. Breadth: mine implementation, docs, tests, history, releases, issues, PRs, discussions, roadmaps, and provenance—not only README claims.
    6. Spirit: explore transferable principles and responsible extensions even when upstream has only a partial prototype; label inference separately from shipped fact.

    Exhaustive, dated source ledger

    For a repository-shaped source inspect canonical docs/design/API examples; code, tests, fixtures, and configuration at a pinned revision; releases/tags/changelog and relevant history/blame; open and closed issues; merged, closed, and open PRs plus review discussion; discussions, RFCs, ADRs, roadmaps, and TODOs; exact-revision LICENSE, per-file headers, NOTICE, vendored/generated provenance, submodules, and contribution terms. For papers/products/standards use equivalent primary sources (artifact/appendix, official release history, normative revision/errata). Follow citations to the mechanism's origin. Inaccessible surfaces are omissions, not empty results.

    Record every material observation with:

    • observed_at: full ISO date/time for the research observation;
    • source_event_at: commit, merge, release, publication, or update date;
    • source state: released/shipped, merged-unreleased, proposed/open, rejected/closed, experimental, or unclear;
    • immutable anchor: path:line@full-sha, release/tag+digest, paper version/DOI, or standards rev;
    • platform context: relevant version, API generation, provider, hardware, plan/tier, or environment;
    • refresh trigger: release, PR merge, API rollover, benchmark rerun, or none known.

    Never write timeless “X does Y” for a changing platform. Open issues, PRs, and roadmaps prove interest/direction, not shipped behavior.

    License disposition: copy when allowed

    Read the license at the exact studied revision and check per-file/NOTICE/provenance boundaries. Classify every candidate before implementation:

    • DIRECT-PORT: copying/modification is permitted and obligations fit. Prefer copying the smallest coherent implementation or test, preserving notices and source path@sha, then adapt.
    • ADAPT: reuse is permitted but fak interfaces, dependencies, or constraints require material changes. Identify direct versus rewritten portions and retain attribution.
    • INSPIRE-ONLY: terms are absent, unclear, incompatible, proprietary, or behavior-only. Build independently; do not copy expressive code, tests, comments, or assets.
    • DO-NOT-USE: provenance or terms are unsafe; exclude and record why.

    Do not default to inspire-only because clean-room rewriting feels cleaner. Public visibility also does not grant permission. When obligations are ambiguous, use INSPIRE-ONLY or seek review.

    Expansive candidate extraction

    Extract all of these before ranking:

    • direct mechanisms: algorithms, schemas, tests, UX, operations, and documentation;
    • negative knowledge: reverts, rejected proposals, recurring issue failures, regressions, reviews;
    • emerging direction: open PRs, issues, RFCs, roadmaps, TODOs, and design sketches, marked proposed;
    • Spirit extensions: infer the broader principle and adjacent fak applications, using source fact -> inferred principle -> fak opportunity -> disconfirming check;
    • combinations across independent sources that produce a stronger design.

    Be expansive in discovery and conservative in claims. A promising unimplemented idea is a valid INFERENCE when paired with a cheap experiment/falsifier; it is not parity evidence.

    Bounded-superset portfolio rule

    The target is not "copy the winner" and not "accumulate every feature." It is a bounded capability superset: within fak's declared scope and support budget, users should be able to trust that fak carries the strongest reasonable industry default and preserves materially useful alternatives for cohorts whose constraints differ. fak is egoless about where those capabilities originated. Its modular leaf/adapter/integration boundaries are an advantage: a useful alternative need not displace the default or contaminate the kernel core.

    For every witnessed capability, record one portfolio disposition:

    DispositionUse whenRequired form
    DEFAULTstrongest net-true choice for the common supported caseintegrated, documented default with a witness against the real alternative
    OPTIONAL-MODULEuseful for a named user/job/constraint but not the broad defaultisolated leaf, adapter, policy, backend, or integration; explicit opt-in and support owner
    RECIPEuseful and supportable, but too narrow or environment-specific to ship as maintained codetested composition/integration guide with prerequisites and dated witness
    WATCHpromising, moment-in-time, immature, or evidence is not strong enough to support yetdated source + review trigger; no shipped claim
    EXCLUDEoutside scope, unsafe, license-incompatible, operationally unaffordable, or genuinely dominatednamed reason and the evidence/disconfirming condition that could reopen it

    DEFAULT is not the only successful outcome. Do not reject a capability merely because a different technique wins overall, is newer, or is already fak's default. Ask whether a real supported cohort still benefits under a constraint such as hardware, provider, latency, quality, privacy, deployment topology, compatibility, cost, or operator preference. If yes, prefer an OPTIONAL-MODULE or RECIPE seam over deletion. Conversely, age, popularity, or "someone might want it" is not enough: an obviously superseded approach with no surviving cohort goes to EXCLUDE, and a fast-moving snapshot goes to WATCH until revalidated.

    Each non-excluded row must name: capability axis; user/job/constraint served; observed evidence and date; relationship to the default; proposed modular seam; incremental build, test, security, documentation, and maintenance cost; owner or review trigger; and a witness that would disconfirm usefulness. This is the reasonable-coverage budget. Once marginal support cost exceeds witnessed user value, stop expanding and register the omission instead of boiling the ocean.

    A study is coverage-complete only when it reports both:

    1. Default frontier — where fak's common-case default should lead or change.
    2. Coverage frontier — useful supported cohorts still absent even though the default may already be best overall.

    Required completion evidence

    In addition to the PRESENT/PARTIAL/ABSENT self-query pass below, completion requires a coverage checklist, dated source ledger, license disposition, candidate matrix (fact versus inference and shipped versus proposed), exact fak seam, and either shipped proof or contract-ready filed work. Prefer shipping a safe in-scope minimal spine now over reflexively creating backlog. A long link list is not exhaustive research: state what each source changed in the conclusion.

    Why this skill exists

    fak researches the outward field well — the docs/notes/RESEARCH-* corpus, industry-score, idea-scout, sota-check all point outward. But applying a field idea inward has a silent failure mode: an agent reads "Cognee does GraphRAG" or "Zep has bi-temporal memory" and files "fak should add graph memory" without first asking fak whether it already has it — so the tracker accretes gaps fak already closed, or gaps described one abstraction away from the real seam. The research was outward-complete but the witness step was manual and skipped.

    The law, in one line: the default answer to "does fak already have this field-standard capability?" is ask fak, don't assume — dogfood the self-query surface to witness present / partial / absent, then file only the witnessed gaps, each grounded in a seam.

    This is the loop that produced #3161 / #3162 / #3163 (edge-aware query, retrieval-eval, freshness rung) under epic #1494: three retrieval-quality gaps borrowed from Cognee/Zep, LongMemEval/LOCOMO, and Zep/Mem0 — each witnessed by querying fak_feature_query against fak's own internal/selfquery before filing, each grounded at internal/selfquery/selfquery.go (the flat lexical ranker at :566). See docs/notes/CONCEPT-FIELD-BORROW-QUERY-QUALITY-2026-07-08.md for that worked instance.

    How this differs from its siblings (do not duplicate them)

    Skill / toolDirectionMechanismFiles issues?Dogfoods the self-query witness?
    sota-checkinward, kernels onlyfak sota <op> prior-art matrixnono
    industry-scoreoutwardscorecard: coverage + parity-debt over a taxonomynono
    idea-scout (tools/idea_scout.py)outward, automatedarXiv/GitHub scan, dedup vs existing issues (seen-cache · body-stamp · title-Jaccard)yes (triage queue)no (issue-vs-issue only, never capability-vs-codebase)
    field-borrow (this)outward→inwarddogfood fak_feature_query to witness the gap, then file epic-anchoredyes (grounded, under the right epic)yes — this is the point

    field-borrow composes with all three: it can be the human-in-the-loop pass over an idea-scout hit, it feeds witnessed coverage rows to industry-score, and once a spine ships it hands off to spine-fanout.

    The pass

    1 — Name the source and the capability axis (dated)

    Pick ONE capability from a named external system or a dated source: an agent-memory product (Letta/MemGPT, Mem0, Zep/Graphiti, Cognee, Supermemory), a serving system (vLLM/SGLang/TensorRT-LLM), a competitor feature, a benchmark (LongMemEval, LOCOMO), or a row from the RESEARCH-* / industry field scans. Write it down with the source, so the borrow is falsifiable: "Zep/Graphiti — bi-temporal edges: facts carry validity windows; a newer fact invalidates the old one." One capability per pass; do not batch.

    2 — Dogfood the self-query WITNESS (the heart of this skill)

    Ask fak, three ways, whether it already has the capability — do not reason about it from memory:

    • fak_feature_query (MCP) / fak capabilities <intent> — intent → ranked capability cards (name, summary, witness content-address, the call to make).
    • fak index docs|leaves|verbs|claims <terms> — the dev self-index over docs, packages, CLI verbs, and the CLAIMS ledger.
    • Also a plain Grep for the concept's obvious symbol, to catch a capability the lexical ranker missed (see Honest limits).

    Classify the result, and paste the top cards as the witness:

    • PRESENT — a card / verb / leaf directly does it. Read it and confirm it truly does (not just a name collision). PRESENT is a valid, complete, good outcome — "fak already has this, here is the card" ends the pass; do not file.
    • PARTIAL — an adjacent surface exists but not this capability (e.g. fak_index_freshness covers index↔tree drift but not semantic supersession).
    • ABSENT — the query surfaces nothing on-point. An ABSENT claim must show the query that returned nothing on-point — that null result is the falsifiable witness.

    3 — Ground the PARTIAL/ABSENT in a seam (file:line)

    The capability cards point at the code. Find the exact file:line the capability would touch and quote one dogfood result as the in-issue evidence — e.g. the flat lexical ranker score() at internal/selfquery/selfquery.go:566, or the FeatureCard struct at :37 that carries no freshness/edge field. No file:line seam, no issue — a gap you cannot locate is not ready to file; keep witnessing until you can point at the code.

    4 — Dedup, then file grounded (under the right epic)

    Search existing issues and the natural parent epic before filing (avoid re-filing what idea-scout or a human already opened). File under the epic with, in order:

    1. the pain, in fak's terms, quoting the seam from step 3;
    2. the named external inspiration (dated — a fabricated "system X does Y" is the exact citation failure dos_citation_resolve exists to catch);
    3. the dogfood witness from step 2 (the query + what it returned);
    4. a concrete first checkable step (the smallest thing that proves the gap is real and the fix is buildable);
    5. honest fences (deterministic / advisory / read-only where they apply).

    Set milestone + labels at creation. On this host, run gh via PowerShell or the Bash tool deliberately (quote bodies through --body-file, not inline heredocs that the shell mangles).

    5 — Register the trail (or it lives only in a transcript)

    Record the instance in a dated docs/notes/CONCEPT-<topic>-<date>.md: source → witness → seam → filed issues, with a Companions: block. Add its INDEX.md line in the Notes & research section (an unindexed dated note is an orphan fak index freshness flags). Link the children from the parent epic. This registration — not the issues alone — is what makes the research path durable.

    6 — (optional) Feed the map

    A witnessed PRESENT/PARTIAL/ABSENT is a coverage row industry-score can absorb; a genuinely novel, spine-shaped gap can seed spine-fanout once a working spine ships.

    What "done" proves

    • Every filed gap carries a dogfood witness (the query + its top cards), a file:line seam, a named dated external source, and a first checkable step.
    • No gap was filed that fak already ships (step 2 caught the PRESENT cases).
    • The instance is registered: a dated docs/notes entry, its INDEX.md line, and the epic links its children. python tools/... freshness / fak index freshness reads clean for the new note.

    The anti-gaming rule (specific to this surface)

    Never file a capability gap you did not dogfood-witness, and never mark ABSENT without the null query. The witness is the falsifiable record — the way sota-check's Prior-art: trailer is. Two failure modes this rule kills:

    • Assumed-absent. Filing "fak lacks X" from memory when fak_feature_query would have returned the card. The fix is the query, pasted.
    • Fabricated borrow. "Zep does bi-temporal invalidation" when it does not, or citing a system/paper you did not read. Name the source, dated; if you could find no prior art, say that so the next person can disprove it.

    PRESENT is not a failed pass — a witnessed "we already have this" is a real result.

    Where this misleads / honest limits

    • The self-query score is lexical. rankCards/score() (internal/selfquery/selfquery.go:540,566) is strings.Contains substring matching over name/tags/ref/summary — a poorly-phrased query can miss a card fak does have, producing a false-ABSENT. Read the top cards, vary the phrasing, and cross-check with a raw Grep before trusting an ABSENT. (This limit is itself issue #3162 — the ranker is ungraded.)
    • ABSENT means "fak's own index doesn't surface it", not "it doesn't exist." The index can be stale or the capability can live under a name you didn't guess.
    • The witness is a snapshot. A card added tomorrow changes the verdict (the freshness problem is issue #3163). Re-witness before acting on an old pass.
    • Composes with, does not replace: idea-scout (automated outward feeder), industry-score (the competitive coverage map), spine-fanout (post-spine fan-out), sota-check (kernel prior-art). If the capability is a compute kernel, use sota-check instead — this pass is for product / agent / memory / serving capabilities.

    When to run this

    • Reading a RESEARCH-* / SOTA / competitor note and wondering "do we already have this?"
    • Before filing any "fak should add X" capability-gap issue.
    • After a competitor or a paper ships a capability worth borrowing.
    • On a /loop cadence over the docs/notes/RESEARCH-* corpus, to convert inert research into witnessed, grounded, epic-anchored backlog — the inward, human-curated complement to the daily idea-scout.

    Frequently asked questions

    What to verify before installation and use

    What does the field-borrow source document cover?

    High-priority default "inspired by" workflow. Invoke proactively whenever an external product, repository, paper, standard, benchmark, release, issue, PR, roadmap, design discussion, or field practice could improve fak—not only on explicit borrow requests.

    How do I install field-borrow?

    The source record exposes this install command: npx skills add https://github.com/anthony-chaudhary/fak --skill ".claude/skills/field-borrow". Inspect the command and pinned source before running it.

    Alternatives

    Compare before choosing

    Computed 96156

    open-edge-platform/edge-ai-libraries

    chatqna-helm-deploy

    Deploy Chat Question-and-Answer Core to Kubernetes using Helm (OpenVINO CPU, OpenVINO GPU, or Ollama), including values.yaml configuration, helm install/upgrade, deployment verification, uninstall, and translation from Docker Compose setup_env.sh variables into Helm override values. Use this skill when the user says "deploy chatqna core to kubernetes", "helm install chatqna-core", "configure values.yaml", "convert compose config to helm", or "translate setup_env.sh to chart values".

    Computed 9439,098

    wshobson/agents

    brand-landingpage

    Brand-first landing page designer — runs a brand-identity interview (colors, typography, shape language), then generates and iterates on a polished landing page via Stitch with deployment-ready HTML. Use when the user asks to create, design, or build a landing page, homepage, or marketing page and has no established visual direction. Skip when they have a design mockup, need a dashboard or app UI, are working at component level, building a multi-page app, or restyling with known design tokens —

    Computed 9357

    oaslananka/kicad-mcp-pro

    code-review

    Use this skill for GitHub Copilot pull request and code reviews in oaslananka/kicad-mcp-pro. Review Python MCP server changes, KiCad adapter and tool-contract changes, tests, npm/package wrappers, Tauri/Rust desktop code, GitHub Actions, security controls, documentation, generated metadata, and compatibility/release surfaces. Use it whenever reviewing a PR or diff in this repository, especially changes under src/, tests/, packages/, src-tauri/, .github/workflows/, or public MCP metadata/configur

    Computed 92149

    UiPath/skills

    uipath-rpa

    Always invoke for `.xaml` or `.cs` workflow files. UiPath RPA — create, edit, build, run, debug `.cs` coded workflows and `.xaml` workflows. UI automation with Object Repository selectors, test case authoring, Integration Service connector calls. Live desktop/browser UI exploration and control. Deploy via `.uipx`→uipath-solution. Non-solution Orchestrator ops→uipath-platform. Test reports→uipath-test. Agents→uipath-agents.