--- name: grepai description: "Workspace-first GrepAI search workflow for programming agents (v0.34+): project-scoped semantic search, token-efficient output, and reliable fallbacks." --- # GrepAI Workspace Search (Agent-Focused) Use this skill when you need to find code by intent in one or more projects inside a GrepAI workspace. ## Scope and Priority - Primary tool for intent-based code search: `grepai search`. - Primary context model: `--workspace ` with optional `--project `. - Use exact-text tools only for exact literals, symbol names, or imports. Semantic intent examples: - "where authentication is enforced" - "how retries are handled" - "where config is loaded and validated" Exact-text examples (do not use semantic search): - exact function name - exact env var key - exact import statement ## Current CLI Facts (v0.34.0) - `grepai search` supports `--workspace `. - `grepai search` supports repeatable `--project ` (`stringArray`). - `grepai search` supports `--path ` to constrain results. - `grepai search` supports `--limit ` for result count. - `grepai search` supports `--json` and `--toon` output modes. - `--compact` requires `--json` or `--toon`. - `grepai workspace` provides multi-project management. - Workspace storage backends are `postgres` or `qdrant` (not GOB). ## Agent Defaults Use these defaults unless the user asks otherwise: - Output mode: `--toon --compact` for token efficiency. - Scope: always include `--workspace`; add `--project` when known. - Query language: English. - Query style: describe behavior and intent, not symbol spelling. ## Standard Workflow 1. Verify GrepAI availability and workspace context. ```bash grepai version grepai workspace status Projects ``` 2. Ensure the workspace is indexed and current. ```bash grepai workspace status Projects ``` If workspace metadata or index data is missing, report it and ask the user to run workspace/index setup tasks. 3. Run an initial scoped semantic search. ```bash grepai search --workspace Projects --project "$(get-project)" \ "request validation and auth checks" --toon --compact --limit 8 ``` 4. Refine scope and phrasing iteratively. ```bash # Multi-project search (repeat --project) grepai search --workspace Projects --project api --project web \ "JWT refresh token rotation" --toon --compact --limit 10 # Restrict to path prefix inside indexed project(s) grepai search --workspace Projects --project api --path src/auth \ "authorization failure handling" --toon --compact --limit 10 ``` 5. Open top results for full context, then optionally use trace. ```bash grepai trace callers "ValidateToken" \ --workspace Projects --project api --toon grepai trace callees "HandleLogin" \ --workspace Projects --project api --toon ``` ## Query Quality Rules Good query examples: - `user authentication middleware and token validation` - `database retry logic with backoff` - `startup config loading from environment` Bad query examples: - `auth` - `function` - exact symbol names (use exact-text search for those) Guidelines: - 3 to 7 words is usually best. - Prefer behavior and outcomes over syntax. ## Output Mode Selection - `--toon --compact`: default for AI-agent loops. - `--json --compact`: when downstream tooling needs JSON parsing. - Human-readable output: manual debugging only. ## Troubleshooting and Recovery 1. Workspace missing (`no grepai project found` style errors). Report the missing workspace and ask the user to create/add projects. Do not run `workspace create`, `workspace add`, `workspace remove`, or `workspace delete` as part of this skill. 2. Empty index (`files/chunks = 0`) or stale results. ```bash grepai workspace status Projects ``` If the index is empty or stale, report it and ask the user to run indexing. 3. Watcher uncertainty in background mode. Report watcher/daemon issues and ask the user to restart watcher services. 4. Embedder/provider failures. Verify provider endpoint and model. If using OpenAI provider, verify API key presence. ## Fallback Policy If GrepAI is unavailable or still returns unusable results after setup checks: 1. State the failure mode clearly. 2. Fall back to exact/file-pattern tooling to keep progress. 3. Keep follow-up file reads tightly scoped. ## Quick Command Set ```bash # Agent baseline (workspace + single project) grepai search --workspace Projects --project "$(get-project)" \ "input validation and error mapping" --toon --compact --limit 8 # Cross-project search (subset) grepai search --workspace Projects --project core --project cli \ "configuration merge precedence" --toon --compact --limit 10 # JSON compact for scriptable pipelines grepai search --workspace Projects --project "$(get-project)" \ "retry policy implementation" --json --compact --limit 5 ``` ## Keywords grepai, workspace search, semantic code search, project-scoped search, toon, compact, agent workflow, token-efficient search, cross-project exploration