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kitaru-adapter-builder
Build a project-local Kitaru adapter for an unsupported Python or TypeScript agent framework. Use when a user wants to record or replay framework-native agent runs in Kitaru, needs a custom adapter, has no supported Kitaru integration for their framework, or needs to assess wheth
Übersicht
Build a project-local Kitaru adapter for an unsupported Python or TypeScript agent framework. Use when a user wants to record or replay framework-native agent runs in Kitaru, needs a custom adapter, has no supported Kitaru integration for their framework, or needs to assess whether public framework hooks and the installed Kitaru SDK can support an adapter.
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Kitaru adapter builder
Build the smallest honest adapter inside the user's project. Preserve the framework's public entrypoint and report exactly what the adapter can observe, record, replay, and recover from.
Do not assume every framework can support the same fidelity. A useful result is either a locally tested adapter or a precise blocker tied to the installed versions and public hooks.
Core contract
- Start with read-only inspection of the user's project and installed packages.
- Prefer supported Kitaru adapters, importers, or OTLP export when they meet the requested recording and replay needs. Do not create a duplicate integration.
- Treat the user's installed SDK and framework as authority. Use Kitaru reference adapters as patterns, not as source to copy or as proof of a published API.
- Use only public framework hooks. Offer a coarser boundary or stop when complete coverage would require private internals.
- Implement in the user's project first. Do not edit Kitaru core or prepare an upstream contribution unless the user separately approves that work.
- Keep per-run session IDs, clients, node indexes, buffers, replay state, and framework context isolated. Never store invocation state on a shared wrapper.
- Treat a partially recorded run as partial or failed evidence. Never call it a complete trace because the application returned successfully.
- Treat replay as execution, not a transaction. Block unknown or write-capable side effects unless the selected policy and user approval make them safe.
- Never install dependencies, call credentialed providers, create a remote Kitaru session, execute write-capable tools, or publish changes without the relevant approval.
- Run every Kitaru CLI command and SDK script with
KITARU_ACTIVE_SKILL=kitaru-adapter-builderset so the server attributes the resulting activity to this skill. - Start or restart a user-controlled worker with
--concurrency 10. UseKITARU_WORKER_CONCURRENCY=10only when the launch surface exposes worker settings through environment variables instead of CLI options.
Route from the project
Begin in the project that contains the real agent entrypoint.
- Read the repository instructions and inspect the working tree. Preserve all existing and concurrent changes.
- Identify the package manager, lockfile, runtime, language, framework and version, Kitaru package and version, public agent entrypoint, and invocation modes the application actually uses.
- Route by the entrypoint's runtime:
- For Python, read the Python adapter reference.
- For TypeScript, read the TypeScript adapter reference.
- For another runtime, stop with an unsupported-language report.
- Read the adapter method, search the project, installed packages, and current Kitaru documentation for a compatible adapter, importer, or OTLP path, and create the adapter assessment before editing code.
- Read validation and reporting before finalizing the design or writing tests.
In a mixed repository, route from the process that executes the agent. Do not load both language references merely because both languages exist somewhere in the repository.
If the framework already exports traces in a format no built-in importer
supports and that post-hoc evidence meets the user's goal, continue with
kitaru-importer-builder instead of wrapping the live entrypoint. Carry forward
the repository and revision, public entrypoint, framework and version, export
source and shape, Kitaru package and version, target agent and version, and
requested evidence. Choose this route once; do not bounce back merely because
the importer mentions an adapter as an alternative.
Establish the requested fidelity
Separate these questions before choosing an implementation:
| Question | Possible answer |
|---|---|
| Recording boundary | Whole invocation, turn, model step, tool call, subagent call, or coarser span |
| Replay tier | Input rerun, turn replay, framework-native boundary replay, finer checkpoint replay, or not claimed |
| Tool visibility | Local tools, MCP tools, provider-native tools, hidden framework tools, or unknown |
| Invocation modes | Async, sync, streaming, manual iteration, batch, handoff, resume, interrupt, or durable execution |
| Failure policy | Kitaru failure fails the invocation, or recording is best effort with an explicit degraded result |
Do not use “replay” without naming the tier. Running the same root input again is an input rerun, not deterministic replay.
For streaming, keep three claims separate:
- the application still yields tokens or events;
- the adapter observes the stream through completion, failure, cancellation, and abandonment;
- replay reproduces the original chunks or timing.
Supporting one does not prove the others.
Stop before writing code when necessary
Stop and give the exact reason when any of these apply:
- a compatible existing adapter, importer, or OTLP route satisfies the request;
- the project is not Python or TypeScript;
- no usable public Kitaru SDK contract is installed or approved for installation;
- the framework exposes no public hook at the required boundary;
- the only Python entrypoint is synchronous and the available Kitaru contract is async, with no documented safe async framework hook;
- the requested behavior depends on hidden provider or framework activity;
- replay safety requires match cardinality, occurrence identity, or another Kitaru contract the installed SDK does not expose;
- an incomplete imported baseline cannot prove the calls needed for effectful replay;
- the required dependency is unpublished and the user has not approved a local tarball or workspace-link path.
Do not replace a missing SDK contract with handwritten REST calls, an improvised event-loop bridge, private framework imports, or copied draft plugin code.
Use explicit approval gates
Read-only discovery does not need a separate approval. Ask before each action that changes the user's environment or external state:
| Action | Required approval |
|---|---|
| Install or change a dependency | Exact package, version, and package-manager command |
| Use a local unpublished TypeScript artifact | Exact tarball or workspace-link path |
| Call a model or other credentialed provider | Provider, expected calls, and cost or data consequence |
| Create a remote Kitaru session | Endpoint, tenant, captured categories, and test purpose |
| Permit live tool passthrough | Exact tools, effect class, and miss condition |
| Prepare an OSS contribution | Target repository, files, and contribution scope |
Approval for one row does not authorize another.
Implement in bounded checkpoints
Use this order:
- Confirm the public framework hook with a deterministic local probe.
- Freeze the adapter assessment and capability claims.
- Implement per-run state and the session/root lifecycle.
- Add model, tool, subagent, and stream observation only where public hooks prove it.
- Add replay only after the baseline-admissibility and side-effect gates pass.
- Define bounded, allowlisted payload projections before broad serialization.
- Test success, primary application failure, Kitaru write failure, concurrency, cancellation, and every claimed replay policy with fakes.
- Inspect the recorded session and node tree rather than trusting only the application result.
- Produce the capability report.
Keep the framework's public signature, return value, configured callbacks, exception behavior, and type surface intact. If preserving them is not possible, report the API change before implementing it.
Handle failures as evidence
Preserve the first application or adapter failure. Attempt terminal failure recording without masking that failure, and report later recording or cleanup errors separately.
If session creation succeeds and a later write fails:
- retain already confirmed nodes;
- record the last confirmed write;
- try to mark the root and session failed;
- do not claim the trace is complete;
- apply the adapter's documented Kitaru-availability policy to the application invocation.
An incomplete imported trace is a replay-input problem here. Assess it and stop unsafe replay. Do not repair or redesign the importer inside this skill.
Resume safely
On a resumed run, re-read the project, working tree, installed versions, adapter assessment, and tests. Recheck that the chosen hooks and SDK symbols still exist. Do not overwrite user changes or repeat dependency installation and remote smoke tests merely because an earlier transcript is unavailable.
Finish with an honest handoff
Use the capability-report format in validation and reporting. State what was verified with fakes, what was verified against a real Kitaru session, and what remains unsupported or unverified.
After every claimed mode passes locally, offer a separate optional contribution step. Do not imply that a project-local adapter is upstream-ready merely because the happy path works.
Dateimetadaten
name: kitaru-adapter-builder description: Build a project-local Kitaru adapter for an unsupported Python or TypeScript agent framework. Use when a user wants to record or replay framework-native agent runs in Kitaru, needs a custom adapter, has no supported Kitaru integration for their framework, or needs to assess whether public framework hooks and the installed Kitaru SDK can support an adapter.
Originaltext anzeigen
---
name: kitaru-adapter-builder
description: Build a project-local Kitaru adapter for an unsupported Python or TypeScript agent framework. Use when a user wants to record or replay framework-native agent runs in Kitaru, needs a custom adapter, has no supported Kitaru integration for their framework, or needs to assess whether public framework hooks and the installed Kitaru SDK can support an adapter.
---
# Kitaru adapter builder
Build the smallest honest adapter inside the user's project. Preserve the
framework's public entrypoint and report exactly what the adapter can observe,
record, replay, and recover from.
Do not assume every framework can support the same fidelity. A useful result is
either a locally tested adapter or a precise blocker tied to the installed
versions and public hooks.
## Core contract
- Start with read-only inspection of the user's project and installed packages.
- Prefer supported Kitaru adapters, importers, or OTLP export when they meet the
requested recording and replay needs. Do not create a duplicate integration.
- Treat the user's installed SDK and framework as authority. Use Kitaru reference
adapters as patterns, not as source to copy or as proof of a published API.
- Use only public framework hooks. Offer a coarser boundary or stop when complete
coverage would require private internals.
- Implement in the user's project first. Do not edit Kitaru core or prepare an
upstream contribution unless the user separately approves that work.
- Keep per-run session IDs, clients, node indexes, buffers, replay state, and
framework context isolated. Never store invocation state on a shared wrapper.
- Treat a partially recorded run as partial or failed evidence. Never call it a
complete trace because the application returned successfully.
- Treat replay as execution, not a transaction. Block unknown or write-capable
side effects unless the selected policy and user approval make them safe.
- Never install dependencies, call credentialed providers, create a remote Kitaru
session, execute write-capable tools, or publish changes without the relevant
approval.
- Run every Kitaru CLI command and SDK script with
`KITARU_ACTIVE_SKILL=kitaru-adapter-builder` set so the server attributes the
resulting activity to this skill.
- Start or restart a user-controlled worker with `--concurrency 10`. Use
`KITARU_WORKER_CONCURRENCY=10` only when the launch surface exposes worker
settings through environment variables instead of CLI options.
## Route from the project
Begin in the project that contains the real agent entrypoint.
1. Read the repository instructions and inspect the working tree. Preserve all
existing and concurrent changes.
2. Identify the package manager, lockfile, runtime, language, framework and
version, Kitaru package and version, public agent entrypoint, and invocation
modes the application actually uses.
3. Route by the entrypoint's runtime:
- For Python, read [the Python adapter reference](references/python-adapters.md).
- For TypeScript, read
[the TypeScript adapter reference](references/typescript-adapters.md).
- For another runtime, stop with an unsupported-language report.
4. Read [the adapter method](references/adapter-method.md), search the project,
installed packages, and current Kitaru documentation for a compatible
adapter, importer, or OTLP path, and create the adapter assessment before
editing code.
5. Read [validation and reporting](references/validation-and-reporting.md) before
finalizing the design or writing tests.
In a mixed repository, route from the process that executes the agent. Do not
load both language references merely because both languages exist somewhere in
the repository.
If the framework already exports traces in a format no built-in importer
supports and that post-hoc evidence meets the user's goal, continue with
`kitaru-importer-builder` instead of wrapping the live entrypoint. Carry forward
the repository and revision, public entrypoint, framework and version, export
source and shape, Kitaru package and version, target agent and version, and
requested evidence. Choose this route once; do not bounce back merely because
the importer mentions an adapter as an alternative.
## Establish the requested fidelity
Separate these questions before choosing an implementation:
| Question | Possible answer |
|---|---|
| Recording boundary | Whole invocation, turn, model step, tool call, subagent call, or coarser span |
| Replay tier | Input rerun, turn replay, framework-native boundary replay, finer checkpoint replay, or not claimed |
| Tool visibility | Local tools, MCP tools, provider-native tools, hidden framework tools, or unknown |
| Invocation modes | Async, sync, streaming, manual iteration, batch, handoff, resume, interrupt, or durable execution |
| Failure policy | Kitaru failure fails the invocation, or recording is best effort with an explicit degraded result |
Do not use “replay” without naming the tier. Running the same root input again is
an input rerun, not deterministic replay.
For streaming, keep three claims separate:
1. the application still yields tokens or events;
2. the adapter observes the stream through completion, failure, cancellation,
and abandonment;
3. replay reproduces the original chunks or timing.
Supporting one does not prove the others.
## Stop before writing code when necessary
Stop and give the exact reason when any of these apply:
- a compatible existing adapter, importer, or OTLP route satisfies the request;
- the project is not Python or TypeScript;
- no usable public Kitaru SDK contract is installed or approved for installation;
- the framework exposes no public hook at the required boundary;
- the only Python entrypoint is synchronous and the available Kitaru contract is
async, with no documented safe async framework hook;
- the requested behavior depends on hidden provider or framework activity;
- replay safety requires match cardinality, occurrence identity, or another
Kitaru contract the installed SDK does not expose;
- an incomplete imported baseline cannot prove the calls needed for effectful
replay;
- the required dependency is unpublished and the user has not approved a local
tarball or workspace-link path.
Do not replace a missing SDK contract with handwritten REST calls, an improvised
event-loop bridge, private framework imports, or copied draft plugin code.
## Use explicit approval gates
Read-only discovery does not need a separate approval. Ask before each action
that changes the user's environment or external state:
| Action | Required approval |
|---|---|
| Install or change a dependency | Exact package, version, and package-manager command |
| Use a local unpublished TypeScript artifact | Exact tarball or workspace-link path |
| Call a model or other credentialed provider | Provider, expected calls, and cost or data consequence |
| Create a remote Kitaru session | Endpoint, tenant, captured categories, and test purpose |
| Permit live tool passthrough | Exact tools, effect class, and miss condition |
| Prepare an OSS contribution | Target repository, files, and contribution scope |
Approval for one row does not authorize another.
## Implement in bounded checkpoints
Use this order:
1. Confirm the public framework hook with a deterministic local probe.
2. Freeze the adapter assessment and capability claims.
3. Implement per-run state and the session/root lifecycle.
4. Add model, tool, subagent, and stream observation only where public hooks
prove it.
5. Add replay only after the baseline-admissibility and side-effect gates pass.
6. Define bounded, allowlisted payload projections before broad serialization.
7. Test success, primary application failure, Kitaru write failure, concurrency,
cancellation, and every claimed replay policy with fakes.
8. Inspect the recorded session and node tree rather than trusting only the
application result.
9. Produce the capability report.
Keep the framework's public signature, return value, configured callbacks,
exception behavior, and type surface intact. If preserving them is not possible,
report the API change before implementing it.
## Handle failures as evidence
Preserve the first application or adapter failure. Attempt terminal failure
recording without masking that failure, and report later recording or cleanup
errors separately.
If session creation succeeds and a later write fails:
- retain already confirmed nodes;
- record the last confirmed write;
- try to mark the root and session failed;
- do not claim the trace is complete;
- apply the adapter's documented Kitaru-availability policy to the application
invocation.
An incomplete imported trace is a replay-input problem here. Assess it and stop
unsafe replay. Do not repair or redesign the importer inside this skill.
## Resume safely
On a resumed run, re-read the project, working tree, installed versions, adapter
assessment, and tests. Recheck that the chosen hooks and SDK symbols still exist.
Do not overwrite user changes or repeat dependency installation and remote smoke
tests merely because an earlier transcript is unavailable.
## Finish with an honest handoff
Use the capability-report format in
[validation and reporting](references/validation-and-reporting.md). State what
was verified with fakes, what was verified against a real Kitaru session, and
what remains unsupported or unverified.
After every claimed mode passes locally, offer a separate optional contribution
step. Do not imply that a project-local adapter is upstream-ready merely because
the happy path works.
Quelle prüfen
Preis und Betriebskosten
- Skill beziehen
- Preis unbestätigt
- Ausführen
- Anforderungen unbestätigt. Agenten-, API- und Dienstkosten an der Quelle prüfen.
- Lizenz
- Apache-2.0
- Preis unbestätigt
- Der Preis ist noch nicht bestätigt. Vorhandene Quell- und Installationslinks bleiben verfügbar.
Kostenloser Bezug bedeutet nicht kostenlosen Betrieb. Preise sind keine Sicherheitsbewertung. Preisinformation einreichen →
Skill-Quelle erfasst
Ein Anleitungspfad ist erfasst. Das ist kein Ausführungstest und keine Sicherheits- oder Kompatibilitätsgarantie.
Vor Installation prüfen: Automatische Installation vermeiden
Lizenz: Apache-2.0
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Financial research output is not financial advice; require human review before any live investment decision
- KI-Prüffreigabe fehlt
- Financial research output is not financial advice; require human review before any live investment decision.
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
- Review status: AI review approval is missing
Tools sind Metadatenhinweise, keine getestete Kompatibilität. Prompts sind Vorschläge.
Mit einer kleinen Aufgabe beginnen
- 1Quelle lesen und Eingaben, Ergebnisse, Abhängigkeiten sowie Berechtigungen prüfen.
- 2Agent um einen Plan bitten. Einrichtung und Kosten vor einem isolierten Test genehmigen.
- 3Ergebnisse und geänderte Dateien prüfen. Nur tatsächliche Ausführungen melden und die Quellrevision aufbewahren.
Prüfe Abhängigkeiten, API-Schlüssel und externe Kosten in der Quelle. Öffentliche Repositories bedeuten nicht, dass alle Dienste kostenlos sind.
Quelle und Nutzungshinweise
ErfasstStatisch geprüft
Metadaten und Prüfungen dienen der Orientierung. Beliebtheit, Quellenerfassung und erfolgreiche Ausführung sind verschiedene Fakten.
- Quell-Repository
- decodingai-magazine/building-a-coding-agent-from-scratch-course
- Lizenz
- Apache-2.0
- Version
- Unknown
- Letzter GitHub-Push
- 15. Sept. 2026
- Verzeichnis aktualisiert
- 15. Sept. 2026
Version aus den Verzeichnismetadaten; Releases der Quelle prüfen.
Qualität
68/100
Vielversprechend
Vertrauen
63/100
Nur Sandbox
Audit
76/100
Prüfung nötig
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Financial research output is not financial advice; require human review before any live investment decision
- KI-Prüffreigabe fehlt
- Financial research output is not financial advice; require human review before any live investment decision.
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
- Review status: AI review approval is missing
- Verified installs
- —
- Ergebnisse
- —
Kopieren ist keine Installation. Zahlen benötigen eine Erfolgsmeldung und garantieren keine allgemeine Qualität.
Agent-Zugang
Die Registry API stellt Entscheidungs-, Vertrauens-, Audit-, Use-Case- und Installationssignale ohne UI-Scraping bereit.
Weitere Details
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"stars": "415 GitHub stars",
"repoActivity": "415 stars, 113 forks",
"lastPushed": "27d since push",
"license": "Apache-2.0",
"repository": "https://github.com/decodingai-magazine/building-a-coding-agent-from-scratch-course/tree/main/.agents/skills/kitaru-adapter-builder",
"install": "npx skills add decodingai-magazine/building-a-coding-agent-from-scratch-course --skill kitaru-adapter-builder",
"installSafety": "standard package or runtime install path",
"permissionSurface": "secrets or environment access, shell or command execution",
"documentation": "Strong README/SKILL.md context",
"agentOutcomes": "No agent outcome data yet"
},
"outcome_evidence": {
"total": 0,
"successes": 0,
"failures": 0,
"not_relevant": 0,
"success_rate": null,
"recent_success_rate": null,
"recent_failure_rate": null,
"install_attempts": 0,
"install_success_rate": null,
"risk_blocked": 0,
"setup_required": 0,
"avg_output_quality": null,
"production_outcomes": 0,
"last_outcome_at": null,
"label": "No agent outcome data yet"
},
"auto_install": {
"allowed": false,
"sandbox_required": true,
"reason": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
},
"best_for": [
"design-creative",
"agent-skill"
],
"known_risks": [
"AI review approval is missing",
"Financial research output is not financial advice; require human review before any live investment decision.",
"Quality score needs review",
"Permission surface needs review: secrets or environment access, shell or command execution",
"Dependency/runtime risk: command execution surface, credential or environment access",
"Permission surface: secrets or environment access, shell or command execution",
"Review status: AI review approval is missing"
]
},
"agent_proven": {
"version": "agent-proven-v1",
"score": 0,
"tier": "unproven",
"label": "Needs first agent run",
"summary": "No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.",
"metrics": {
"totalOutcomes": 0,
"successfulOutcomes": 0,
"failedOutcomes": 0,
"installAttempts": 0,
"installSuccessRate": null,
"successRate": null,
"recentSuccessRate": null,
"recentFailureRate": null,
"riskBlocked": 0,
"setupRequired": 0,
"notRelevant": 0,
"avgOutputQuality": null,
"avgTimeToUsefulMs": null,
"productionOutcomes": 0,
"humanReviewRequired": 0,
"uniqueAgents": 0,
"lastOutcomeAt": null
},
"signals": [],
"penalties": [
"No real agent outcome evidence yet"
]
},
"audit": {
"score": 76,
"risk_level": "needs_review",
"risk_label": "Needs review",
"warnings": [
"Dependency or permission surface needs review",
"Permission surface may require sandboxing",
"Financial research output is not financial advice; require human review before any live investment decision",
"AI review approval is missing",
"Financial research output is not financial advice; require human review before any live investment decision.",
"Quality score needs review",
"Permission surface needs review: secrets or environment access, shell or command execution",
"Dependency/runtime risk: command execution surface, credential or environment access"
]
},
"safety_gate": {
"tier": "blocked",
"label": "Blocked for auto-install",
"auto_install_policy": "block",
"auto_install_allowed": false,
"human_review_required": true,
"blocked": true,
"recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
},
"quality": {
"score": 68,
"label": "Promising"
},
"supply": {
"track": "Design and creative production",
"scenario": "Design and creative",
"maintenance": "27d since push",
"risk": "Needs review"
},
"alternative_skills": [],
"do_not_use_when": [
"teams that need a vendor-supported SLA",
"high-compliance environments without internal security review",
"No major risk signals from current metadata",
"High-risk permission hints: Shell or command execution, Secrets or environment access",
"Dependency or permission surface needs review",
"Permission surface may require sandboxing",
"Financial research output is not financial advice; require human review before any live investment decision",
"AI review approval is missing"
],
"agent_contract": {
"task_input": "Use kitaru-adapter-builder in an agent workflow",
"recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
"install_policy": "block",
"minimum_review_before_use": [
"Trust: 71/100 Manual review",
"Audit: 76/100 Needs review",
"Safety: 36/100 Avoid automatic install",
"Review repository, license, install command, and permission surface before production use."
],
"expected_agent_output": {
"selected_skill": "decodingai-magazine-kitaru-adapter-builder (kitaru-adapter-builder)",
"install_command": "npx skills add decodingai-magazine/building-a-coding-agent-from-scratch-course --skill kitaru-adapter-builder",
"risk_summary": "Needs review; Blocked for auto-install; Review before production",
"verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
}
},
"outcome_feedback": {
"endpoint": "https://www.openagentskill.com/api/agent/outcome",
"method": "POST",
"requires_resolve_event_id": true,
"event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
"expected_outcomes": [
"success",
"failed",
"not_relevant",
"blocked_by_risk",
"setup_required"
],
"payload_template": {
"event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
"skill_slug": "decodingai-magazine-kitaru-adapter-builder",
"task": "Use kitaru-adapter-builder in an agent workflow",
"agent": "codex",
"outcome": "success",
"install_used": true,
"risk_blocked": false,
"setup_required": false,
"task_success": true,
"output_quality": 4,
"error_type": null,
"human_review_required": false,
"workspace": "sandbox",
"time_to_useful_ms": 120000,
"notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
}
},
"endpoints": {
"web": "https://www.openagentskill.com/skills/decodingai-magazine-kitaru-adapter-builder",
"api": "https://www.openagentskill.com/api/agent/skills/decodingai-magazine-kitaru-adapter-builder",
"audit": "https://www.openagentskill.com/skills/decodingai-magazine-kitaru-adapter-builder/audit",
"eval": "https://www.openagentskill.com/api/agent/evals?slug=decodingai-magazine-kitaru-adapter-builder&task=Use%20kitaru-adapter-builder%20in%20an%20agent%20workflow&max_risk=medium",
"resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20kitaru-adapter-builder%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
"receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20kitaru-adapter-builder%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
"install": "https://www.openagentskill.com/api/skills/decodingai-magazine-kitaru-adapter-builder/install",
"manifest": "https://www.openagentskill.com/api/registry/manifest/decodingai-magazine-kitaru-adapter-builder"
}
}Für Ersteller
Quelle des Eintrags
Registry-indexiert
Dieser Eintrag wurde aus öffentlichen Quellen indexiert und ist erst nach Genehmigung eines Maintainer-Anspruchs offiziell.
- Ersteller
- decodingai-magazine
- Indexiert von
- OpenAgentSkill Community-Index
Die Zuordnung verlinkt auf das öffentliche Repository oder Creator-Profil. Creator können den Eintrag beanspruchen, um Eigentümersignale zu aktualisieren.
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Zeige den kanonischen Eintrag, aktuelle Vertrauens- und Audit-Signale sowie echte Agent-Proven-Evidenz dort, wo Entwickler das Repository bewerten.
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[](https://www.openagentskill.com/skills/decodingai-magazine-kitaru-adapter-builder/audit)
[](https://www.openagentskill.com/skills/decodingai-magazine-kitaru-adapter-builder?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)Community-Signal
Teile mit, ob dieser Skill für deinen Agent-Workflow nützlich ist. Zusammengefasstes Feedback verbessert das Ranking im Laufe der Zeit.