find-prompt
Skill53 starsChanged 55 days agoMITView on GitHub
Use when the user names a coding or Claude Code task ("add OAuth", "set up hooks", "review this PR", "pick a model"), asks which prompt to use, says to "use the right prompt", or when you enter this repo and need to orient without reading every file.
In this repository14 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- llms.txtllms.txt
- capability-auditSkill
- changelog-from-commitsSkill
- deterministic-checksSkill
- doc-link-auditSkill
- find-promptSkill
- skill-auditSkill
- capability-auditSkill
- changelog-from-commitsSkill
- deterministic-checksSkill
- doc-link-auditSkill
- skill-auditSkill
The file
We split this skill into the rules it gives an agent
6 rules. About 0 are common, 2 are distinctive, and 4 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
4
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 13
If ${CLAUDE_SKILL_DIR} is not substituted (it shows up literally), fall back: the skill sits next to SKILL.md.
- Very specific: line 17
Determine the task: Use $ARGUMENTS if given. Otherwise use the task already being worked on in this conversation (the user's last real …
- Very specific: line 24
If a path does not exist, tell the user to run /update-prompts and stop.
- Distinctive: line 26
Adopt them and continue: Treat the base prompt as your operating system prompt and the specialist as the domain protocol for this task.
- Distinctive: line 107
Continue, don't restart: After loading, resume the conversation's in-progress work under the new instructions.
- Very specific: line 108
If nothing matches cleanly, read ${CLAUDE_SKILL_DIR}/../../../prompts/english/INDEX.md and route from its task table.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Find the right prompt and run with it
You route the current task to the right file(s) in this library, read them yourself, and then continue the existing work under those instructions — not from scratch, but picking up the conversation and any task already in progress.
${CLAUDE_SKILL_DIR} is this skill's own directory (<library-root>/.claude/skills/find-prompt/). The library root is ${CLAUDE_SKILL_DIR}/../../... All prompt files are under ${CLAUDE_SKILL_DIR}/../../../prompts/english/. Never hardcode an absolute path — always build it from ${CLAUDE_SKILL_DIR} so this works for anyone who clones the library, wherever they put it.
If ${CLAUDE_SKILL_DIR} is not substituted (it shows up literally), fall back: the skill sits next to SKILL.md; run ls up the tree from your working directory to find the folder containing prompts/english/agents/claude-agent-system-prompt.md.
Steps
- Determine the task. Use
$ARGUMENTSif given. Otherwise use the task already being worked on in this conversation (the user's last real request, the in-progress work, the files open). If genuinely unclear, ask one short question and stop. - Match the task to the routing table below. Pick the base prompt plus specialists by tier: 1 for a single-domain task (default), 2 only if the task spans two genuinely independent domains, or route to Multi-Agent Orchestration if the work needs isolation/review. See
${CLAUDE_SKILL_DIR}/../../../prompts/english/workflows/prompt-selector-guide.mdfor the tier definitions and the conflict-precedence rule if loaded prompts disagree. - Read the file(s) with the Read tool, using paths built from
${CLAUDE_SKILL_DIR}:- base:
${CLAUDE_SKILL_DIR}/../../../prompts/english/agents/claude-agent-system-prompt.md - specialist:
${CLAUDE_SKILL_DIR}/../../../prompts/english/<path from the table>If a path does not exist, tell the user to run/update-promptsand stop.
- base:
- Adopt them and continue. Treat the base prompt as your operating system prompt and the specialist as the domain protocol for this task. Then:
- Restate the current task in one line (from the conversation, not invented).
- State the success criteria you'll hold yourself to.
- Carry over every session constraint already established (no git, no server start, static-only, don't touch X, etc.).
- Pick up the work where it stands — continue the in-progress task under the new protocol. Do not restart, do not re-ask what was already answered, do not re-explore what was already explored.
- Confirm in one short block which prompts you loaded and what you're now doing, then proceed.
Routing table
Paths are relative to prompts/english/.
Running Claude Code itself (base prompt not needed — the Claude Code prompt is enough alone)
| Task is about… | Load |
writing / debugging a skill, SKILL.md | agents/agent-skills-prompt.md |
| connecting a DB / browser / API / tool via MCP | agents/mcp-integration-prompt.md |
| a plugin, a marketplace, bundling/sharing config | agents/claude-code-plugins-prompt.md |
| a hook, running something on edit/commit/stop, blocking a command | agents/hooks-automation-prompt.md |
subagents, parallel agents, dynamic workflows, /batch, whole-codebase audit, writer/reviewer | agents/multi-agent-orchestration-prompt.md |
CLAUDE.md, settings.json, .claude/rules, permissions | agents/claude-code-workflow-prompt.md |
effort levels, ultrathink, plan mode, how much to think | agents/claude-code-modes-prompt.md |
| which model to use, Opus vs Sonnet vs Haiku vs Fable, pricing | workflows/model-selection-guide.md |
| what a current Claude Code build can do — plan mode, rewind, headless, surfaces | workflows/claude-code-native-features-guide.md |
building an agent in Python/TS, the Agent SDK, query() | workflows/agent-sdk-guide.md |
| AGENTS.md, one config across Cursor/Codex/Aider, the primary source for a claim | workflows/reference-resources.md |
| evaluating or installing a skill, plugin, MCP server, or agent toolkit | workflows/ecosystem-discovery-guide.md |
Building software (base = Agent System + the one specialist below)
| Task is about… | Specialist |
| web frontend — React/Vue/Angular/Svelte, a page, a component | project-types/web-development-prompt.md |
| a REST/GraphQL/gRPC API, an endpoint, a contract | project-types/api-development-prompt.md (+ agents/api-design-graphql-prompt.md for schema-first design) |
| an end-to-end app, frontend + backend together | agents/fullstack-development-prompt.md |
| iOS / Android / React Native / Flutter / KMP | project-types/mobile-development-prompt.md |
| a desktop app — Tauri / Electron / MAUI / Qt | project-types/desktop-development-prompt.md |
| a data pipeline — ETL, streaming, Kafka, Airflow, dbt | agents/data-engineering-prompt.md |
| an ML model, training, RAG, an LLM feature | project-types/data-science-ml-prompt.md (+ agents/ai-llm-integration-prompt.md for app-side integration) |
| Kubernetes, CI/CD, Terraform/OpenTofu, Docker, Cloudflare | project-types/devops-cicd-prompt.md (+ agents/cloud-infrastructure-prompt.md for multi-region / IaC depth) |
| a database schema, SQL, indexing, a slow query | agents/database-optimization-prompt.md (+ project-types/database-sql-prompt.md for data modeling) |
| a game — Unity / Unreal / Godot / Bevy, netcode | project-types/game-development-prompt.md |
| firmware, embedded, IoT, an MCU, an RTOS | project-types/embedded-iot-prompt.md |
| a smart contract, Solidity, web3, an L2 | project-types/blockchain-web3-prompt.md |
| anything else / language-agnostic | project-types/general-software-development-prompt.md |
Improving existing code (base = Agent System + the one specialist below)
| Task is about… | Specialist |
| reviewing a PR or change set | agents/code-review-prompt.md. Also load agents/ui-design-systems-prompt.md if the change touches UI, or agents/security-audit-prompt.md if it touches auth/data. If git is available and you can see the diff, /code-review (the bundled skill) is an option too. |
| security — a vulnerability, threat model, auth, secrets | agents/security-audit-prompt.md |
| a production incident, "it's broken", root cause, a bug | agents/debugging-troubleshooting-prompt.md |
| reducing complexity or technical debt, cleaning up | agents/refactoring-prompt.md |
| adding tests, a test strategy, coverage, a flaky test | agents/testing-strategies-prompt.md |
| slowness — latency, throughput, cost, memory, bundle size | agents/performance-optimization-prompt.md |
| migrating a framework/runtime/DB, a major version bump | agents/migration-upgrade-prompt.md |
| logs, metrics, traces, alerting, observability | agents/monitoring-observability-prompt.md |
| fault tolerance — retries, circuit breakers, resilience | agents/error-handling-resilience-prompt.md |
| accessibility — WCAG, screen readers, a11y | agents/accessibility-audit-prompt.md |
Deciding (base = Agent System + the one specialist below)
| Task is about… | Specialist |
| system design, an architecture pattern, trade-offs | agents/architecture-patterns-prompt.md |
| choosing a tool or library — "what should I use for X" | agents/technology-stack-prompt.md |
| GDPR / HIPAA / SOC 2 / PCI, regulated scope | agents/compliance-governance-prompt.md |
| branching, commits, the release process | agents/git-version-control-prompt.md |
| DX, linting, onboarding, the dev environment | agents/developer-experience-tooling-prompt.md |
| a monorepo, multi-package coordination, Turborepo/Nx | agents/monorepo-complex-projects-prompt.md |
| writing docs, a README, API reference | agents/documentation-prompt.md |
| a design system, tokens, a component library, theming | agents/ui-design-systems-prompt.md |
| consequential research, source verification, product/service comparison, recommendation beyond coding | agents/evidence-driven-research-prompt.md |
Rules
- Composition by tier, not a hard cap. Tier 1 (base + 1 specialist) covers most tasks. Move to Tier 2 (base + 2 specialists) only when the task genuinely spans two independent domains — say so explicitly. Route to Multi-Agent Orchestration (Tier 3) when the work needs isolated workers or adversarial review.
- The base is always
agents/claude-agent-system-prompt.md, except for a task purely about running Claude Code (then the single Claude Code prompt is enough). - Tiny task (typo, rename, one-line fix): don't load anything — say so and do it.
- Continue, don't restart. After loading, resume the conversation's in-progress work under the new instructions. Keep every fact, decision, and constraint already established.
- If nothing matches cleanly, read
${CLAUDE_SKILL_DIR}/../../../prompts/english/INDEX.mdand route from its task table.
Confirmation block (output this, then keep working)
Loaded: agents/claude-agent-system-prompt.md + <specialist path> [+ <optional second>]
Task (continuing): <one line, from the conversation>
Success criteria: <measurable>
Constraints carried over: <list, or "none">Then proceed with the task under the loaded protocol — from where it stands, not from zero.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

