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orient
Orient a developer to an unfamiliar codebase by systematically exploring its structure, purpose, features, conventions, and workflows. Produces a concise orient
Übersicht
Orient a developer to an unfamiliar codebase by systematically exploring its structure, purpose, features, conventions, and workflows. Produces a concise orientation document. Use when the user says "orient me", "what does this project do", "walk me through this codebase", "help me understand this repo", "onboard me", "give me the lay of the land", "codebase overview", or any variation of wanting to quickly understand a project they're new to.
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Orient
Systematically explore a codebase and produce a structured orientation that tells a developer everything they need to start working productively. Depth scales with project size — small projects get a tight summary, large projects get a layered map.
Phase 1 — Project Identity
Establish what the project is before reading any source code.
Read top-level files (in order of priority)
README.md/README— stated purpose, setup instructions, feature listAGENTS.md— architecture boundaries, "always do / never do" rules.cursor/rules/— workspace conventions for this project- Manifest file —
package.json,pyproject.toml,Cargo.toml,go.mod,pom.xml,Gemfile,composer.json, or equivalent CONTRIBUTING.md,ARCHITECTURE.md,docs/index — if present
Extract
- One-sentence purpose: What does this project do, for whom?
- Domain: What problem space does it operate in?
- Stage: Early build, growth, or mature/stable?
- Key dependencies: Frameworks, databases, external services
If the README is absent or unhelpful, infer purpose from the manifest description field, directory names, and import patterns.
Phase 2 — Shape
Map the physical layout without reading file contents yet.
# Get directory tree (depth 2–3 depending on project size)
find . -type f | head -200
# or
tree -L 3 -I 'node_modules|.git|dist|build|__pycache__|venv|.venv|target'
Categorize top-level directories
| Role | Common names | What to look for |
|---|---|---|
| Source | src/, lib/, app/, pkg/, internal/ | Production code |
| Tests | test/, tests/, spec/, __tests__/ | Test suites |
| Config | Root dotfiles, config/, .github/ | Build/CI/lint config |
| Docs | docs/, doc/, wiki/ | Documentation |
| Infra | infra/, deploy/, terraform/, k8s/, docker/ | Deployment |
| Scripts | scripts/, bin/, tools/ | Automation helpers |
| Generated | dist/, build/, out/, target/ | Build artifacts (skip) |
Identify the tech stack
From manifest files and directory structure, determine:
- Language(s) and version constraints
- Framework(s) — web, CLI, library, monorepo tooling
- Database / storage layer
- Build system and package manager
- CI/CD platform (from
.github/workflows/,.gitlab-ci.yml, etc.)
Phase 3 — Architecture
Now read code — but strategically. The goal is to understand the skeleton, not every function.
Scaling strategy
| Project size | Approach |
|---|---|
| Small (≤20 files) | Read every source file. Full picture is cheap. |
| Medium (21–100 files) | Read entry points + 3–5 core modules. Skim the rest by name/export. |
| Large (>100 files) | Read entry points, trace one request/command end-to-end, read the 5 highest-import-count modules. |
Find entry points
Look for:
main.ts,index.ts,app.ts,server.ts— web/API entrymain.py,app.py,__main__.py,manage.py— Python entrymain.go,cmd/— Go entrysrc/main.rs,src/lib.rs— Rust entrybin/scripts, CLI definitionspackage.json"main","bin","exports"fields- Framework-specific:
pages/,app/(Next.js),routes/(Express/Rails)
Trace the skeleton
From entry points, follow the import graph to identify:
- Core modules — where the main logic lives
- Data layer — models, schemas, database access
- API surface — routes, handlers, controllers, exported functions
- Shared utilities — helpers used across modules
- Configuration — how settings flow into the system
Read 3–5 pivotal files fully to understand the primary abstraction patterns.
Identify boundaries
- Monorepo packages / workspaces
- Service boundaries (if microservices)
- Plugin / extension points
- Public API vs internal implementation
Phase 4 — Features and Functionality
Shift from code structure to user/consumer perspective.
For applications (web, CLI, desktop)
Enumerate:
- User-facing features (routes, pages, commands)
- Authentication / authorization model
- Data inputs and outputs
- Background jobs, workers, scheduled tasks
- External integrations (APIs, webhooks, third-party services)
For libraries / SDKs
Enumerate:
- Public exports and their purpose
- Primary use cases (from README examples or test files)
- Extension points (plugins, middleware, hooks)
- Versioning / compatibility guarantees
For infrastructure / tooling
Enumerate:
- What it provisions or manages
- Configuration surface (env vars, config files, CLI flags)
- Operational commands (deploy, rollback, scale)
Phase 5 — Conventions and Patterns
Extract the implicit rules that make contributions consistent.
Look for
- Naming: File naming (kebab, camel, pascal), variable/function style
- Code organization: Feature-based vs layer-based, barrel exports
- Error handling: Custom error types, Result patterns, try/catch strategy
- Testing: Unit vs integration split, fixture patterns, mocking approach
- State management: Where state lives, how it flows
- Type patterns: Strict vs loose typing, shared type definitions
- Logging / observability: Structured logging, tracing, metrics
Sources of truth (in priority order)
AGENTS.mdexplicit rules.cursor/rules/files- Linter/formatter config (
.eslintrc,prettier,ruff.toml,clippy) - Existing code patterns (what the majority of files actually do)
When explicit rules conflict with existing code, note the discrepancy.
Phase 6 — Developer Workflows
Document the practical "how do I..." answers.
Essential workflows to cover
| Workflow | Where to find it |
|---|---|
| Install dependencies | README, manifest lockfile presence |
| Run locally | README, scripts in package.json, Makefile, docker-compose.yml |
| Run tests | test script, CI config, test framework config |
| Build / compile | build script, build tool config |
| Lint / format | lint script, pre-commit hooks, editor config |
| Deploy | CI/CD config, deploy scripts, infra/ directory |
| Add a new feature | CONTRIBUTING.md, existing PR patterns |
Environment setup
Note any required:
- Environment variables (from
.env.example,.env.template, docs) - External services (databases, queues, caches)
- System-level dependencies (specific runtime versions, native libs)
Output
Present findings as a structured orientation document. Adapt depth to what the project warrants — a 10-file CLI tool does not need the same treatment as a 200-file web platform.
Format
# [Project Name] — Orientation
## What this project does
[One paragraph: purpose, domain, users/consumers, stage]
## Tech stack
[Language, framework, database, key dependencies — bullet list]
## Project structure
[Directory map with role annotations — only meaningful directories]
## Architecture
[How components connect. Entry points → core logic → data layer.
Include a brief data flow description for the primary use case.]
## Key features
[Bulleted list of what the project does from a user/consumer perspective]
## Conventions
[Naming, patterns, testing approach, error handling — the implicit rules]
## Developer workflows
[How to: install, run, test, build, deploy — with actual commands]
## Caveats and gotchas
[Anything surprising, non-obvious, or likely to trip up a new contributor]
Adaptation rules
- Skip empty sections. If there's no infra directory, don't fabricate a deployment section.
- Flag unknowns. If something is unclear from the code alone, say so rather than guessing.
- Prioritize actionability. A new developer should be able to start working after reading this.
- Keep it concise. Target 1–2 pages for small projects, 3–4 for large ones. Link to existing docs rather than reproducing them.
Principles
- Read before you conclude. Every claim about the project should be grounded in something you actually read, not inferred from the name.
- Shape before depth. Understand the map before zooming into any territory.
- User perspective matters. Features are what the project does, not how the code is organized.
- Flag, don't fabricate. If the README is stale or docs are missing, say so.
- Respect existing documentation. Point to it rather than restating it when it's accurate and current.
Dateimetadaten
name: orient description: >- Orient a developer to an unfamiliar codebase by systematically exploring its structure, purpose, features, conventions, and workflows. Produces a concise orientation document. Use when the user says "orient me", "what does this project do", "walk me through this codebase", "help me understand this repo", "onboard me", "give me the lay of the land", "codebase overview", or any variation of wanting to quickly understand a project they're new to. license: MIT metadata: author: jcottam version: "1.0.0"
Originaltext anzeigen
--- name: orient description: >- Orient a developer to an unfamiliar codebase by systematically exploring its structure, purpose, features, conventions, and workflows. Produces a concise orientation document. Use when the user says "orient me", "what does this project do", "walk me through this codebase", "help me understand this repo", "onboard me", "give me the lay of the land", "codebase overview", or any variation of wanting to quickly understand a project they're new to. license: MIT metadata: author: jcottam version: "1.0.0" --- # Orient Systematically explore a codebase and produce a structured orientation that tells a developer everything they need to start working productively. Depth scales with project size — small projects get a tight summary, large projects get a layered map. ## Phase 1 — Project Identity Establish what the project *is* before reading any source code. ### Read top-level files (in order of priority) 1. `README.md` / `README` — stated purpose, setup instructions, feature list 2. `AGENTS.md` — architecture boundaries, "always do / never do" rules 3. `.cursor/rules/` — workspace conventions for this project 4. Manifest file — `package.json`, `pyproject.toml`, `Cargo.toml`, `go.mod`, `pom.xml`, `Gemfile`, `composer.json`, or equivalent 5. `CONTRIBUTING.md`, `ARCHITECTURE.md`, `docs/` index — if present ### Extract - **One-sentence purpose**: What does this project do, for whom? - **Domain**: What problem space does it operate in? - **Stage**: Early build, growth, or mature/stable? - **Key dependencies**: Frameworks, databases, external services If the README is absent or unhelpful, infer purpose from the manifest description field, directory names, and import patterns. ## Phase 2 — Shape Map the physical layout without reading file contents yet. ```bash # Get directory tree (depth 2–3 depending on project size) find . -type f | head -200 # or tree -L 3 -I 'node_modules|.git|dist|build|__pycache__|venv|.venv|target' ``` ### Categorize top-level directories | Role | Common names | What to look for | |------|-------------|------------------| | Source | `src/`, `lib/`, `app/`, `pkg/`, `internal/` | Production code | | Tests | `test/`, `tests/`, `spec/`, `__tests__/` | Test suites | | Config | Root dotfiles, `config/`, `.github/` | Build/CI/lint config | | Docs | `docs/`, `doc/`, `wiki/` | Documentation | | Infra | `infra/`, `deploy/`, `terraform/`, `k8s/`, `docker/` | Deployment | | Scripts | `scripts/`, `bin/`, `tools/` | Automation helpers | | Generated | `dist/`, `build/`, `out/`, `target/` | Build artifacts (skip) | ### Identify the tech stack From manifest files and directory structure, determine: - Language(s) and version constraints - Framework(s) — web, CLI, library, monorepo tooling - Database / storage layer - Build system and package manager - CI/CD platform (from `.github/workflows/`, `.gitlab-ci.yml`, etc.) ## Phase 3 — Architecture Now read code — but strategically. The goal is to understand the skeleton, not every function. ### Scaling strategy | Project size | Approach | |--------------|----------| | **Small** (≤20 files) | Read every source file. Full picture is cheap. | | **Medium** (21–100 files) | Read entry points + 3–5 core modules. Skim the rest by name/export. | | **Large** (>100 files) | Read entry points, trace one request/command end-to-end, read the 5 highest-import-count modules. | ### Find entry points Look for: - `main.ts`, `index.ts`, `app.ts`, `server.ts` — web/API entry - `main.py`, `app.py`, `__main__.py`, `manage.py` — Python entry - `main.go`, `cmd/` — Go entry - `src/main.rs`, `src/lib.rs` — Rust entry - `bin/` scripts, CLI definitions - `package.json` `"main"`, `"bin"`, `"exports"` fields - Framework-specific: `pages/`, `app/` (Next.js), `routes/` (Express/Rails) ### Trace the skeleton From entry points, follow the import graph to identify: - **Core modules** — where the main logic lives - **Data layer** — models, schemas, database access - **API surface** — routes, handlers, controllers, exported functions - **Shared utilities** — helpers used across modules - **Configuration** — how settings flow into the system Read 3–5 pivotal files fully to understand the primary abstraction patterns. ### Identify boundaries - Monorepo packages / workspaces - Service boundaries (if microservices) - Plugin / extension points - Public API vs internal implementation ## Phase 4 — Features and Functionality Shift from code structure to user/consumer perspective. ### For applications (web, CLI, desktop) Enumerate: - User-facing features (routes, pages, commands) - Authentication / authorization model - Data inputs and outputs - Background jobs, workers, scheduled tasks - External integrations (APIs, webhooks, third-party services) ### For libraries / SDKs Enumerate: - Public exports and their purpose - Primary use cases (from README examples or test files) - Extension points (plugins, middleware, hooks) - Versioning / compatibility guarantees ### For infrastructure / tooling Enumerate: - What it provisions or manages - Configuration surface (env vars, config files, CLI flags) - Operational commands (deploy, rollback, scale) ## Phase 5 — Conventions and Patterns Extract the implicit rules that make contributions consistent. ### Look for - **Naming**: File naming (kebab, camel, pascal), variable/function style - **Code organization**: Feature-based vs layer-based, barrel exports - **Error handling**: Custom error types, Result patterns, try/catch strategy - **Testing**: Unit vs integration split, fixture patterns, mocking approach - **State management**: Where state lives, how it flows - **Type patterns**: Strict vs loose typing, shared type definitions - **Logging / observability**: Structured logging, tracing, metrics ### Sources of truth (in priority order) 1. `AGENTS.md` explicit rules 2. `.cursor/rules/` files 3. Linter/formatter config (`.eslintrc`, `prettier`, `ruff.toml`, `clippy`) 4. Existing code patterns (what the majority of files actually do) When explicit rules conflict with existing code, note the discrepancy. ## Phase 6 — Developer Workflows Document the practical "how do I..." answers. ### Essential workflows to cover | Workflow | Where to find it | |----------|-----------------| | Install dependencies | README, manifest lockfile presence | | Run locally | README, `scripts` in package.json, `Makefile`, `docker-compose.yml` | | Run tests | `test` script, CI config, test framework config | | Build / compile | `build` script, build tool config | | Lint / format | `lint` script, pre-commit hooks, editor config | | Deploy | CI/CD config, deploy scripts, `infra/` directory | | Add a new feature | CONTRIBUTING.md, existing PR patterns | ### Environment setup Note any required: - Environment variables (from `.env.example`, `.env.template`, docs) - External services (databases, queues, caches) - System-level dependencies (specific runtime versions, native libs) ## Output Present findings as a structured orientation document. Adapt depth to what the project warrants — a 10-file CLI tool does not need the same treatment as a 200-file web platform. ### Format ```markdown # [Project Name] — Orientation ## What this project does [One paragraph: purpose, domain, users/consumers, stage] ## Tech stack [Language, framework, database, key dependencies — bullet list] ## Project structure [Directory map with role annotations — only meaningful directories] ## Architecture [How components connect. Entry points → core logic → data layer. Include a brief data flow description for the primary use case.] ## Key features [Bulleted list of what the project does from a user/consumer perspective] ## Conventions [Naming, patterns, testing approach, error handling — the implicit rules] ## Developer workflows [How to: install, run, test, build, deploy — with actual commands] ## Caveats and gotchas [Anything surprising, non-obvious, or likely to trip up a new contributor] ``` ### Adaptation rules - **Skip empty sections.** If there's no infra directory, don't fabricate a deployment section. - **Flag unknowns.** If something is unclear from the code alone, say so rather than guessing. - **Prioritize actionability.** A new developer should be able to start working after reading this. - **Keep it concise.** Target 1–2 pages for small projects, 3–4 for large ones. Link to existing docs rather than reproducing them. ## Principles - Read before you conclude. Every claim about the project should be grounded in something you actually read, not inferred from the name. - Shape before depth. Understand the map before zooming into any territory. - User perspective matters. Features are what the project does, not how the code is organized. - Flag, don't fabricate. If the README is stale or docs are missing, say so. - Respect existing documentation. Point to it rather than restating it when it's accurate and current.
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Kostenloser Bezug bedeutet nicht kostenlosen Betrieb. Preise sind keine Sicherheitsbewertung. Preisinformation einreichen →
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Ein Anleitungspfad ist erfasst. Das ist kein Ausführungstest und keine Sicherheits- oder Kompatibilitätsgarantie.
Vor Installation prüfen: Automatische Installation vermeiden
Lizenz: MIT
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Low GitHub adoption signal
- KI-Prüffreigabe fehlt
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- GitHub adoption: 30 GitHub stars
- Stars/forks activity: 30 stars, 1 forks; issue activity unavailable in current metadata
- 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
- jcottam/agent-resources
- Lizenz
- MIT
- Version
- 1.0.0
- Letzter GitHub-Push
- 6. Aug. 2026
- Verzeichnis aktualisiert
- 9. Okt. 2026
- Anleitungspfad
- skills/engineering/orient/SKILL.md @ 2152ad14c00c
Version aus den Verzeichnismetadaten; Releases der Quelle prüfen.
Qualität
50/100
Prüfung nötig
Vertrauen
57/100
Do not auto-install
Audit
67/100
Prüfung nötig
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Low GitHub adoption signal
- KI-Prüffreigabe fehlt
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- GitHub adoption: 30 GitHub stars
- Stars/forks activity: 30 stars, 1 forks; issue activity unavailable in current metadata
- 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
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Weitere Details
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"stars": "30 GitHub stars",
"repoActivity": "30 stars, 1 forks",
"lastPushed": "2mo since push",
"license": "MIT",
"repository": "https://github.com/jcottam/agent-resources/tree/main/skills/engineering/orient",
"install": "npx skills add jcottam/agent-resources --skill orient",
"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": [
"automation",
"agent-skill"
],
"known_risks": [
"AI review approval is missing",
"Low GitHub adoption signal",
"Quality score needs review",
"Permission surface needs review: secrets or environment access, shell or command execution",
"GitHub adoption: 30 GitHub stars",
"Stars/forks activity: 30 stars, 1 forks; issue activity unavailable in current metadata",
"Dependency/runtime risk: command execution surface, credential or environment access",
"Permission surface: secrets or environment access, shell or command execution"
]
},
"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": 67,
"risk_level": "needs_review",
"risk_label": "Needs review",
"warnings": [
"Dependency or permission surface needs review",
"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: 30 GitHub stars",
"Stars/forks activity: 30 stars, 1 forks; issue activity unavailable in current metadata"
]
},
"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": 50,
"label": "Needs review"
},
"supply": {
"track": "Research and knowledge work",
"scenario": "RAG and knowledge",
"maintenance": "2mo 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",
"Dependency or permission surface needs review",
"Permission surface may require sandboxing",
"AI review approval is missing",
"Quality score needs review"
],
"agent_contract": {
"task_input": "Use orient 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: 65/100 Manual review",
"Audit: 67/100 Needs review",
"Safety: 23/100 Avoid automatic install",
"Review repository, license, install command, and permission surface before production use."
],
"expected_agent_output": {
"selected_skill": "jcottam-orient (orient)",
"install_command": "npx skills add jcottam/agent-resources --skill orient",
"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": "jcottam-orient",
"task": "Use orient 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/jcottam-orient",
"api": "https://www.openagentskill.com/api/agent/skills/jcottam-orient",
"audit": "https://www.openagentskill.com/skills/jcottam-orient/audit",
"eval": "https://www.openagentskill.com/api/agent/evals?slug=jcottam-orient&task=Use%20orient%20in%20an%20agent%20workflow&max_risk=medium",
"resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20orient%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
"receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20orient%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
"install": "https://www.openagentskill.com/api/skills/jcottam-orient/install",
"manifest": "https://www.openagentskill.com/api/registry/manifest/jcottam-orient"
}
}Für Ersteller
Quelle des Eintrags
Registry-indexiert
Dieser Eintrag wurde aus öffentlichen Quellen indexiert und ist erst nach Genehmigung eines Maintainer-Anspruchs offiziell.
- Ersteller
- jcottam
- Quelle
- jcottam/agent-resources
- Indexiert von
- OpenAgentSkill Community-Index
Die Zuordnung verlinkt auf das öffentliche Repository oder Creator-Profil. Creator können den Eintrag beanspruchen, um Eigentümersignale zu aktualisieren.
Diesen Skill beanspruchenEigentümeranspruch
Diesen Skill-Eintrag beanspruchen
Dieser Registry-indexiert-Eintrag wird jcottam zugeschrieben, ist aber noch nicht offiziell markiert. Beanspruche ihn, um ein verifiziertes Eigentümersignal hinzuzufügen und künftige Launch-, Installations- und Audit-Updates vertrauenswürdiger zu machen.
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Zeige den kanonischen Eintrag, aktuelle Vertrauens- und Audit-Signale sowie echte Agent-Proven-Evidenz dort, wo Entwickler das Repository bewerten.
[](https://www.openagentskill.com/skills/jcottam-orient?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/jcottam-orient?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/jcottam-orient/audit)
[](https://www.openagentskill.com/skills/jcottam-orient?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.