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adopt-existing

Source-first growth of an existing single- or multi-repository project into CYPRESS's unified docs/graph knowledge system. Use from initialize when code already exists, or for a graph refresh after material code changes. Scout executable evidence, model subsystem nodes, build pro

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价格未确认★ 43 GitHub Stars目录更新于 · 2026年9月30日agent-skill

概览

Source-first growth of an existing single- or multi-repository project into CYPRESS's unified docs/graph knowledge system. Use from initialize when code already exists, or for a graph refresh after material code changes. Scout executable evidence, model subsystem nodes, build project-specific architecture/product/API/data/dependency/prompt/operations leaves, connect them for progressive discovery, and validate navigation. Never trust centralized prose without source corroboration, invent specs or ADRs, modify application files, run application builds, or push Git.

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Adopt an existing project

Turn a generic installed seed into a project-specific knowledge plant. Follow docs/graph/protocols/initialize.md; this skill supplies the existing-project discovery and authoring discipline.

Invariants

  • docs/graph/ is the only maintained knowledge root. The router, nodes, LLM wiki, provenance, plans, runbooks, contracts, and deep dives are layers of this one graph (rule.knowledge).
  • Executable source outranks prose. Manifests, entry points, routes, schemas, migrations, config, deployment, tests, CI, prompts, and evals are primary evidence. Existing docs are corroborating evidence only.
  • Make additive knowledge changes. Preserve application code and unrelated existing files. Leave competing AI configurations in place; deleting or relocating one is the owner's call.
  • Adoption ONLY records build and test commands: extract each exact command and label it discovered, not executed. An inherited suite stays untrusted until proven RED by mutation (docs/graph/protocols/test-first.md), so record it as discovered.
  • Git stays read-only: record the repository revision as provenance; fetch, pull, switch, commit, and push each need a separate explicit request.
  • Record observed behaviour and observed choices as node facts. Specs and ADRs record intent, which only an existing record or the owner supplies. Unknown means unknown.

Scout pass

Establish the governed boundary first: one repo, workspace/monorepo, or an umbrella of sibling repos. For each repository record path, branch, HEAD, worktree state, role, manifests, stack, and the natural language of its identifiers and domain vocabulary. A non-English (or otherwise non-default) language is an explicit graph fact, because downstream agents grep and reason in it and an unrecorded mismatch silently defeats every later search. Boundaries follow capabilities, not repository count.

Inventory cheaply, excluding generated/vendor/cache/build output. Then open the smallest authoritative files needed to trace:

  1. bootstrap and runtime entry points;
  2. module/service/package boundaries and imports;
  3. inbound APIs, messages, scheduled work, and outbound integrations;
  4. entities, schemas, migrations, storage, and data movement;
  5. config/secrets interfaces, deployment, and observability;
  6. tests, CI, scripts, prompts, evaluations, and operational commands;
  7. direct dependencies and evidence of their actual usage.

Return facts with exact paths and symbols. Find source corroboration for each claim prose makes, or record it as untrusted/unverified; repetition across central docs adds no corroboration.

Every delegated worker's brief embeds the canonical block from docs/graph/templates/prompts/graph-session-bootstrap.md.

Librarian pass

Normalize the evidence into single fact owners:

  • configure ROOT_ID and KINDS in docs/graph/graph-lint.py;
  • author a root node and capability/subsystem nodes;
  • factor shared stack, platform, data, domain, and cross-cutting facts into their own nodes only where this reduces duplication;
  • give nodes concrete load_when triggers and source paths;
  • keep requires minimal and acyclic; use peers for boundaries, and composes where an expertise.* node offers sub-expertises the router should descend into only when the task names one;
  • link detailed leaves using artifacts: and dependency wiki pages using libraries:.

Then enrich the leaf collections under docs/graph/:

CollectionSource-grounded content
product/actors, capabilities, flows, observed constraints
architecture/context, components, runtime flows, integrations, sharp edges
api/observed HTTP/RPC/event/job contracts with code locations
data/ownership, schemas, persistence, migrations, lineage
libraries/all direct deps indexed; critical deps richly wikified
sources/provenance for external information actually used
prompts/discovered prompt contracts, versions, and call sites
evaluations/discovered datasets, rubrics, gates, and failure modes
runbooks/exact operational and verification commands, with status
plans/evidence gaps, drift/backfill work, next useful increment
best-practices/conventions demonstrated by this project

Keep specs/ and decisions/ indexes, and fill them only from genuine intent records that already exist and can be preserved with provenance. Put implementation observations in nodes or architecture leaves.

When the sweep confirms zero test or gate infrastructure, write an absent (YYYY-MM-DD) — <reason> row for each standard gate in the verification runbook: a blank runbook is indistinguishable from one nobody checked, and a row for each gate turns an unknown into a stated finding.

When a legacy or parallel documentation source predates and conflicts with the evidence-derived graph, give the exclusion a real, routable node that states (a) the source is excluded as evidence, (b) what supersedes it, and (c) that this is a trust/evidence decision only: the artifact itself stays untouched (Invariants). A silent skip reads to a later agent as no decision, and the artifact gets re-trusted. The Handoff's excluded-docs report then points at this node rather than standing in for it.

Dependency wiki depth

Index every direct dependency from manifests. Create a detailed library page during initialization when the dependency is architecturally significant, security/operations critical, unusual, or used across several subsystems. Each page answers how this project uses it, where configuration lives, relevant constraints, sharp edges, and verification status.

Installed versions come from manifests/locks. Upstream lifecycle, compatibility, or current guidance requires a primary upstream source; otherwise mark it pending rather than guessing. Record consulted sources in docs/graph/sources/.

Refreshing an existing graph

Treat graph prose as a read model to verify against current source:

  1. compare repository revisions with the graph changelog/provenance;
  2. scout changed areas and their dependency/data/API blast radius;
  3. update the existing fact owner instead of creating a duplicate;
  4. preserve valid hand-authored context;
  5. remove or supersede stale seed-owned claims only with cited contrary evidence;
  6. record conflicts and unanswered questions in the plan.

Report a refresh as partial, naming each unavailable source, whenever part of the governed source was out of reach.

Validation

Run knowledge checks only:

python3 docs/graph/graph-lint.py
python3 docs/graph/graph-lint.py --plan "change a representative capability"

Verify all graph links resolve; every Tier-3 leaf is reachable from an owning node; no duplicate fact homes exist; representative task routes are small and relevant; commands say whether they were executed; the verification runbook carries the absent-gate rows where no infrastructure was found (Librarian pass); and no template placeholders, fabricated success, inferred specs, or invented rationale remain.

Use known-answer navigation questions from several capabilities plus an adversarial false-premise question. A wrong or bulk-read answer is a graph defect: improve ownership, routing, or leaf content and rerun, for at most two fix-and-rerun rounds per defect; with the authoring pass they are the three attempts docs/graph/protocols/recover.md allows. A defect that survives them goes to the user as an honest unknown.

Handoff (the stopping condition)

Adoption is done when validation passes within its bounded rounds and the open defects are recorded; completeness is measured by reliable progressive discovery. End with the payload from docs/graph/templates/prompts/handback-payload.md, and report: repository revisions, evidence inspected, graph artifacts created or refreshed, validation outcomes, docs deliberately excluded as untrusted (each named by its exclusion node), remaining unknowns, and one highest-leverage next action with its tier.

文件元数据
name: adopt-existing
description: Source-first growth of an existing single- or multi-repository project into CYPRESS's unified docs/graph knowledge system. Use from initialize when code already exists, or for a graph refresh after material code changes. Scout executable evidence, model subsystem nodes, build project-specific architecture/product/API/data/dependency/prompt/operations leaves, connect them for progressive discovery, and validate navigation. Never trust centralized prose without source corroboration, invent specs or ADRs, modify application files, run application builds, or push Git.
id: skill.adopt-existing
tier: 2
kind: skill
origin: seed
title: adopt-existing — grow an existing codebase into the docs/graph knowledge plant, source-first
owns:
  - adopt-existing.method
  - adopt-existing.refresh
  - adopt-existing.validation
requires:
  - protocol.grow
peers:
  - protocol.initialize
  - skill.knowledge-graph
  - protocol.from-scratch
load_when:
  - "adopt an existing codebase into the graph"
  - "initialize cypress on a project that already has code"
  - "refresh the knowledge graph after material code changes"
  - "onboard a multi-repo or monorepo project"
  - "build docs/graph for existing source"
artifacts:
  - templates/prompts/graph-session-bootstrap.md
  - templates/prompts/handback-payload.md
prevents: An adoption with no way back — a graph authored once from a snapshot of the code, with no refresh path when the source moves under it, so it decays into a confident description of a repository that no longer exists.
est_tokens: 1780
查看原始文本
---
name: adopt-existing
description: Source-first growth of an existing single- or multi-repository project into CYPRESS's unified docs/graph knowledge system. Use from initialize when code already exists, or for a graph refresh after material code changes. Scout executable evidence, model subsystem nodes, build project-specific architecture/product/API/data/dependency/prompt/operations leaves, connect them for progressive discovery, and validate navigation. Never trust centralized prose without source corroboration, invent specs or ADRs, modify application files, run application builds, or push Git.
id: skill.adopt-existing
tier: 2
kind: skill
origin: seed
title: adopt-existing — grow an existing codebase into the docs/graph knowledge plant, source-first
owns:
  - adopt-existing.method
  - adopt-existing.refresh
  - adopt-existing.validation
requires:
  - protocol.grow
peers:
  - protocol.initialize
  - skill.knowledge-graph
  - protocol.from-scratch
load_when:
  - "adopt an existing codebase into the graph"
  - "initialize cypress on a project that already has code"
  - "refresh the knowledge graph after material code changes"
  - "onboard a multi-repo or monorepo project"
  - "build docs/graph for existing source"
artifacts:
  - templates/prompts/graph-session-bootstrap.md
  - templates/prompts/handback-payload.md
prevents: An adoption with no way back — a graph authored once from a snapshot of the code, with no refresh path when the source moves under it, so it decays into a confident description of a repository that no longer exists.
est_tokens: 1780
---

# Adopt an existing project

Turn a generic installed seed into a project-specific knowledge plant.
Follow `docs/graph/protocols/initialize.md`; this skill supplies the
existing-project discovery and authoring discipline.

## Invariants

- `docs/graph/` is the only maintained knowledge root. The router,
  nodes, LLM wiki, provenance, plans, runbooks, contracts, and deep
  dives are layers of this one graph (`rule.knowledge`).
- Executable source outranks prose. Manifests, entry points, routes,
  schemas, migrations, config, deployment, tests, CI, prompts, and evals
  are primary evidence. Existing docs are corroborating evidence only.
- Make additive knowledge changes. Preserve application code and
  unrelated existing files. Leave competing AI configurations in place;
  deleting or relocating one is the owner's call.
- Adoption ONLY records build and test commands: extract each exact
  command and label it `discovered, not executed`. An inherited suite
  stays untrusted until proven RED by mutation
  (`docs/graph/protocols/test-first.md`), so record it as discovered.
- Git stays read-only: record the repository revision as provenance;
  fetch, pull, switch, commit, and push each need a separate explicit
  request.
- Record observed behaviour and observed choices as node facts. Specs
  and ADRs record intent, which only an existing record or the owner
  supplies. Unknown means unknown.

## Scout pass

Establish the governed boundary first: one repo, workspace/monorepo, or
an umbrella of sibling repos. For each repository record path, branch,
HEAD, worktree state, role, manifests, stack, and the natural language
of its identifiers and domain vocabulary. A non-English (or otherwise
non-default) language is an explicit graph fact, because downstream
agents grep and reason in it and an unrecorded mismatch silently defeats
every later search. Boundaries follow capabilities, not repository
count.

Inventory cheaply, excluding generated/vendor/cache/build output. Then
open the smallest authoritative files needed to trace:

1. bootstrap and runtime entry points;
2. module/service/package boundaries and imports;
3. inbound APIs, messages, scheduled work, and outbound integrations;
4. entities, schemas, migrations, storage, and data movement;
5. config/secrets interfaces, deployment, and observability;
6. tests, CI, scripts, prompts, evaluations, and operational commands;
7. direct dependencies and evidence of their actual usage.

Return facts with exact paths and symbols. Find source corroboration for
each claim prose makes, or record it as untrusted/unverified; repetition
across central docs adds no corroboration.

Every delegated worker's brief embeds the canonical block from
`docs/graph/templates/prompts/graph-session-bootstrap.md`.

## Librarian pass

Normalize the evidence into single fact owners:

- configure `ROOT_ID` and `KINDS` in `docs/graph/graph-lint.py`;
- author a root node and capability/subsystem nodes;
- factor shared stack, platform, data, domain, and cross-cutting facts
  into their own nodes only where this reduces duplication;
- give nodes concrete `load_when` triggers and source paths;
- keep `requires` minimal and acyclic; use `peers` for boundaries, and
  `composes` where an `expertise.*` node offers sub-expertises the
  router should descend into only when the task names one;
- link detailed leaves using `artifacts:` and dependency wiki pages
  using `libraries:`.

Then enrich the leaf collections under `docs/graph/`:

| Collection | Source-grounded content |
|---|---|
| `product/` | actors, capabilities, flows, observed constraints |
| `architecture/` | context, components, runtime flows, integrations, sharp edges |
| `api/` | observed HTTP/RPC/event/job contracts with code locations |
| `data/` | ownership, schemas, persistence, migrations, lineage |
| `libraries/` | all direct deps indexed; critical deps richly wikified |
| `sources/` | provenance for external information actually used |
| `prompts/` | discovered prompt contracts, versions, and call sites |
| `evaluations/` | discovered datasets, rubrics, gates, and failure modes |
| `runbooks/` | exact operational and verification commands, with status |
| `plans/` | evidence gaps, drift/backfill work, next useful increment |
| `best-practices/` | conventions demonstrated by this project |

Keep `specs/` and `decisions/` indexes, and fill them only from genuine
intent records that already exist and can be preserved with provenance.
Put implementation observations in nodes or architecture leaves.

When the sweep confirms zero test or gate infrastructure, write an
`absent (YYYY-MM-DD) — <reason>` row for each standard gate in the
verification runbook: a blank runbook is indistinguishable from one
nobody checked, and a row for each gate turns an unknown into a stated
finding.

When a legacy or parallel documentation source predates and conflicts
with the evidence-derived graph, give the exclusion a real, routable
node that states (a) the source is excluded as evidence, (b) what
supersedes it, and (c) that this is a trust/evidence decision only: the
artifact itself stays untouched (Invariants). A silent skip reads to a
later agent as no decision, and the artifact gets re-trusted. The
Handoff's excluded-docs report then points at this node rather than
standing in for it.

## Dependency wiki depth

Index every direct dependency from manifests. Create a detailed library
page during initialization when the dependency is architecturally
significant, security/operations critical, unusual, or used across
several subsystems. Each page answers how this project uses it, where
configuration lives, relevant constraints, sharp edges, and verification
status.

Installed versions come from manifests/locks. Upstream lifecycle,
compatibility, or current guidance requires a primary upstream source;
otherwise mark it pending rather than guessing. Record consulted sources
in `docs/graph/sources/`.

## Refreshing an existing graph

Treat graph prose as a read model to verify against current source:

1. compare repository revisions with the graph changelog/provenance;
2. scout changed areas and their dependency/data/API blast radius;
3. update the existing fact owner instead of creating a duplicate;
4. preserve valid hand-authored context;
5. remove or supersede stale seed-owned claims only with cited contrary
   evidence;
6. record conflicts and unanswered questions in the plan.

Report a refresh as partial, naming each unavailable source, whenever
part of the governed source was out of reach.

## Validation

Run knowledge checks only:

```sh
python3 docs/graph/graph-lint.py
python3 docs/graph/graph-lint.py --plan "change a representative capability"
```

Verify all graph links resolve; every Tier-3 leaf is reachable from an
owning node; no duplicate fact homes exist; representative task routes
are small and relevant; commands say whether they were executed; the
verification runbook carries the absent-gate rows where no
infrastructure was found (Librarian pass); and no template placeholders,
fabricated success, inferred specs, or invented rationale remain.

Use known-answer navigation questions from several capabilities plus an
adversarial false-premise question. A wrong or bulk-read answer is a
graph defect: improve ownership, routing, or leaf content and rerun, for
at most two fix-and-rerun rounds per defect; with the authoring pass
they are the three attempts `docs/graph/protocols/recover.md` allows. A
defect that survives them goes to the user as an honest unknown.

## Handoff (the stopping condition)

Adoption is done when validation passes within its bounded rounds and
the open defects are recorded; completeness is measured by reliable
progressive discovery. End with the payload from
`docs/graph/templates/prompts/handback-payload.md`, and report:
repository revisions, evidence inspected, graph artifacts created or
refreshed, validation outcomes, docs deliberately excluded as untrusted
(each named by its exclusion node), remaining unknowns, and one
highest-leverage next action with its tier.

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已跟踪的来源发生变化或同步失败,请在安装前复核当前来源。

安装前审查: 避免自动安装

许可证: MIT

  • Permission surface may require sandboxing
  • Low GitHub adoption signal
  • 缺少 AI 审查批准
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • GitHub adoption: 43 GitHub stars
  • Stars/forks activity: 43 stars, 1 forks; issue activity unavailable in current metadata
  • Permission surface: secrets or environment access, shell or command execution
  • Review status: AI review approval is missing
打开完整审计

工具列表来自元数据,并非已测试的兼容性;Agent 提示词是建议的交接方式。

从一个小任务开始

  1. 1阅读来源,确认输入、预期输出、依赖和权限。
  2. 2先让 Agent 提出计划,批准环境配置和费用,再进行隔离的小规模测试。
  3. 3检查输出和变更文件,只报告实际执行结果,并保留来源版本以便复现。

请在来源中核实依赖、API 密钥及第三方费用。公开仓库不代表所有服务免费。

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仓库元数据和审核信号仅供参考。受欢迎、已发现来源、成功运行是不同的事实。

来源仓库
llopresto87/Cypress
许可证
MIT
版本
Unknown
最近 GitHub 推送
2026年9月30日
目录更新于
2026年9月30日

版本来自目录元数据,使用前请核实来源发布记录。

质量

58/100

有潜力

信任

62/100

仅限沙盒

审计

73/100

需审查

  • Permission surface may require sandboxing
  • Low GitHub adoption signal
  • 缺少 AI 审查批准
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • GitHub adoption: 43 GitHub stars
  • Stars/forks activity: 43 stars, 1 forks; issue activity unavailable in current metadata
  • Permission surface: secrets or environment access, shell or command execution
  • Review status: AI review approval is missing
Verified installs
—
结果
—

复制不等于安装。安装数需有成功安装回报,不代表全面的质量保证。

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本页通过 Registry API 提供相同的决策、信任、审计、场景和安装信号,让 Agent 无需抓取界面即可排序。

更多详情
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    "reviewed_at": "2026-09-30T23:46:09.323Z",
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    "description": "Source-first growth of an existing single- or multi-repository project into CYPRESS's unified docs/graph knowledge system. Use from initialize when code already exists, or for a graph refresh after material code changes. Scout executable evidence, model subsystem nodes, build project-specific architecture/product/API/data/dependency/prompt/operations leaves, connect them for progressive discovery, and validate navigation. Never trust centralized prose without source corroboration, invent specs or ADRs, modify application files, run application builds, or push Git.",
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    "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": 73,
    "risk_level": "needs_review",
    "risk_label": "Needs review",
    "warnings": [
      "Permission surface may require sandboxing",
      "Low GitHub adoption signal",
      "AI review approval is missing",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "GitHub adoption: 43 GitHub stars",
      "Stars/forks activity: 43 stars, 1 forks; issue activity unavailable in current metadata",
      "Permission surface: secrets or environment access, shell or command execution"
    ]
  },
  "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": 58,
    "label": "Promising"
  },
  "supply": {
    "track": "Research and knowledge work",
    "scenario": "Research agents",
    "maintenance": "13d since push",
    "risk": "Needs review"
  },
  "alternative_skills": [],
  "do_not_use_when": [
    "teams that need a vendor-supported SLA",
    "production agents without a repository review",
    "Low GitHub adoption signal",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Permission surface may require sandboxing",
    "AI review approval is missing",
    "Quality score needs review",
    "Permission surface needs review: secrets or environment access, shell or command execution"
  ],
  "agent_contract": {
    "task_input": "Use adopt-existing 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: 70/100 Manual review",
      "Audit: 73/100 Needs review",
      "Safety: 33/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "llopresto87-adopt-existing (adopt-existing)",
      "install_command": "",
      "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": "llopresto87-adopt-existing",
      "task": "Use adopt-existing 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/llopresto87-adopt-existing",
    "api": "https://www.openagentskill.com/api/agent/skills/llopresto87-adopt-existing",
    "audit": "https://www.openagentskill.com/skills/llopresto87-adopt-existing/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=llopresto87-adopt-existing&task=Use%20adopt-existing%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20adopt-existing%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20adopt-existing%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/llopresto87-adopt-existing/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/llopresto87-adopt-existing"
  }
}

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