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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
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:
- bootstrap and runtime entry points;
- module/service/package boundaries and imports;
- inbound APIs, messages, scheduled work, and outbound integrations;
- entities, schemas, migrations, storage, and data movement;
- config/secrets interfaces, deployment, and observability;
- tests, CI, scripts, prompts, evaluations, and operational commands;
- 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_IDandKINDSindocs/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_whentriggers and source paths; - keep
requiresminimal and acyclic; usepeersfor boundaries, andcomposeswhere anexpertise.*node offers sub-expertises the router should descend into only when the task names one; - link detailed leaves using
artifacts:and dependency wiki pages usinglibraries:.
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:
- compare repository revisions with the graph changelog/provenance;
- scout changed areas and their dependency/data/API blast radius;
- update the existing fact owner instead of creating a duplicate;
- preserve valid hand-authored context;
- remove or supersede stale seed-owned claims only with cited contrary evidence;
- 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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- MIT
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来源需要复核
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
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阅读来源,确认输入、预期输出、依赖和权限。
- 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。
来源与使用须知
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。
Agent 接入
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",
"package_fingerprint": "8bcdc8cc4bd4cc6e4999c283b6bd2b3c30c756b0e652eedb6c02abe77b5efaf5",
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"trust": {
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"installSafety": "standard package or runtime install path",
"permissionSurface": "secrets or environment access, shell or command execution",
"documentation": "Strong README/SKILL.md context",
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"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"
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"AI review approval is missing",
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"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"
]
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"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."
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"quality": {
"score": 58,
"label": "Promising"
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"supply": {
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},
"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"
}
}创作者工具
收录来源
Registry 收录
此列表来自公开来源,维护者认领获批前不会标记为官方。
- 创作者
- llopresto87
- 收录方
- OpenAgentSkill 社区索引
归属链接指向公开仓库或创作者主页。创作者可认领列表以更新所有权信号。
认领此 Skill所有者认领
认领此 Skill 页面
这条 Registry 收录 列表归属于 llopresto87,但尚未标记为官方。认领后可增加已验证所有者信号,使后续发布、安装和审计更新更值得信赖。
分享工具包
创作者外链工具包
将证据徽章加入你的 README
在开发者评估仓库的位置展示规范页面、当前信任与审计信号,以及真实的 Agent 验证证据。
[](https://www.openagentskill.com/skills/llopresto87-adopt-existing?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/llopresto87-adopt-existing?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/llopresto87-adopt-existing/audit)
[](https://www.openagentskill.com/skills/llopresto87-adopt-existing?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)社区信号
告诉我们这个 Skill 是否对你的 Agent 工作流有帮助。汇总反馈会持续改善排序。
