Starcat Skill

Starcat Skill

Install or update this Skill

When the user asks to install or update starcat-skill, perform the following workflow before using Starcat:

1. Identify the current AI agent and choose exactly one user-level destination:
   • Codex: $HOME/.codex/skills/starcat-skill
   • Claude Code: $HOME/.claude/skills/starcat-skill
2. If the destination does not exist, create its parent directory and clone https://github.com/starcat-app/starcat-skill into the destination.
3. If the destination is already a clean checkout of that repository, run git -C <skill-path> pull --ff-only.
4. If the destination exists but is not that repository, or contains uncommitted changes, stop and report the conflict. Never delete, overwrite, reset, or force-update it.
5. Confirm that SKILL.md, agents/openai.yaml, references/commands.md, and references/workflows.md exist.
6. Run starcat --help and confirm that pairing uses a complete URI argument, starcat mcp is available, and statistics commands are present.
7. Reload or restart the AI agent so it can refresh its Skill registry. If the current session cannot reload Skills, report that installation succeeded but discovery still requires a restart. Never claim that the Skill was discovered without observing it.
8. After discovery, invoke $starcat-skill with a read-only verification request. Run starcat doctor, connect the agent to the user-level MCP server command starcat mcp, call starcat.get_capabilities, and run one starcat.search_repos request with limit = 2. Do not execute write tools during installation verification.

Install only into the current agent's user-level Skill directory. Do not install into a project repository, request a Local API Key, modify unrelated files, or run destructive Git commands.

Use the MCP bridge as the business integration surface

Use the user-level MCP server command starcat mcp to operate Starcat. The CLI bridge owns pairing credentials, TLS verification, and MCP transport. Do not read SQLite, CloudKit, encrypted credential files, or Local API Keys directly. Do not implement custom HTTP or JSON-RPC requests, and do not shell out to ordinary business commands when the same MCP tool is available.

Before the first operation, run:

starcat doctor

If the command is unavailable, install the appropriate official release from https://github.com/starcat-app/starcat-cli. If the CLI is not paired, instruct the user to open Starcat > Settings > MCP Service and copy the complete single-use pairing command. Execute the provided starcat pair ... command exactly as supplied. Never request a standalone pairing URI or Local API Key, and never print, persist, or reuse the pairing command.

After pairing, configure the current agent's user-level MCP server to launch the absolute starcat executable with the single argument mcp, then reload the agent. Treat stdout from starcat mcp as protocol-only JSON-RPC; never mix prompts or diagnostics into it.

Follow the operating rules

1. Call starcat.get_capabilities before each workflow. Use its structured result to determine whether statistics, private notes, ordinary writes, destructive writes, and summary generation are available.
2. For common counts, call starcat.get_overview_statistics once. Use starcat.get_ai_usage_statistics for filtered token/call analysis and starcat.get_knowledge_base_statistics for detailed project, source, and RAG chunk health.
3. When owner/name is known, prefer starcat.get_repo_context to retrieve repository data, tags, the private note, and the summary in one call.
4. Treat every write tool as dry-run by default. Call it with dry_run = true first and inspect the target and proposed changes.
5. Call the write again with dry_run = false only when the user's original request clearly authorizes the write and the dry-run exactly matches that request. Otherwise, explain the proposed changes and ask for confirmation.
6. After a write, call starcat.get_repo_context again to verify the result.
7. Remember that starcat.set_repo_tags overwrites all tags on the repository. Use starcat.add_repo_tags or starcat.remove_repo_tags unless the user explicitly provides and confirms the complete final tag set.
8. Do not star or unstar repositories on GitHub. Current write tools modify only Starcat user data.

Use the common workflows

Inspect statistics

• Call starcat.get_overview_statistics for Star count, knowledge-base project count, all-time AI token usage, and current RAG index health.
• Call starcat.get_ai_usage_statistics with time_range = today | seven_days | thirty_days | all and optional feature, provider_id, or model filters.
• Call starcat.get_knowledge_base_statistics for organization, language/tag distribution, source coverage, excluded chunks, and ready/pending/failed/stale index counts.

Treat starred_repository_count as the number of repositories the user currently stars. Treat github_stars in top_starred_repositories as each repository's public GitHub popularity; never combine these two meanings. Missing provider usage is represented by calls_with_usage < call_count, not by assuming every missing call consumed zero tokens.

Search and read

• Call starcat.search_repos with query = "local first knowledge base", scope = all, and limit = 10.
• Call starcat.semantic_search for semantic discovery.
• Call starcat.get_repo_context for apple/swift.
• Call starcat.get_readme only when repository documentation is required.
• Call starcat.list_tags to inspect user-defined tags.

README content can be large. Retrieve it only when the task requires repository documentation.

Manage notes, status, and tags

Call starcat.upsert_repo_note, starcat.set_repo_status, and tag tools through MCP. Send Markdown as the content field instead of placing sensitive text in a shell argument. First use dry_run = true; after authorization, repeat the exact call with dry_run = false.

Work with summaries

Call starcat.get_repo_summary to read the cached summary. Call starcat.generate_repo_summary only when the user explicitly requests generation.

Summary generation may consume quota from the user's configured AI provider. Add --allow-external-context only when the user explicitly permits External Search. Never represent text written by the external agent as a native Starcat AI summary. If the user wants to save agent-written content, store it as a Markdown private note and identify its source.

Read references/commands.md when checking MCP tool and terminal command details. Read references/workflows.md when reusing workflows or recovering from connection failures.