How real projects summarise themselves for language models.
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.
KbWenllms.txtKbWen/agentic-os/llms.txt
agents. It gives agents — Claude Code, OpenAI Codex, Cursor, GitHub Copilot, Google Antigravity, and any Markdown-reading LLM agent — a repeatable plan → build → review → test → ship workflow with quality gates
congminh1254llms.txtcongminh1254/shopee-sdk/llms.txt
ESLint npm run format # Prettier ``` ### Code Quality Tools - **ESLint**: TypeScript-aware linting (`.eslintrc.json`) - **Prettier**: Code formatting (`.prettierrc`) - **Husky**: Git hooks for pre-commit checks - **Commitlint**: Conventional commit messages - **Jest**: Testing
jenticllms.txtjentic/jentic-one/llms.txt
only the operations it has been approved for, and asking for more is a reviewable request rather than a silent widening. - Leave a trail. Every brokered call is recorded
roy-tongllms.txtroy-tong/AgentMeasure/llms.txt
Free local checks for Codex / Claude Code logs and reproducible agent metering verification. Human-delivered diagnostics: $10 Healthcheck and $20 Metering QA. Last reviewed: 2026-10-15. ## Start here - [Website
mihneaptullms.txtmihneaptu/opencode-fusion/site/llms.txt
them. Skills are discovered on demand; installing one needs no restart. 5. Cross-vendor review is emergent: pick main and sidekick from different model families. 6. Only the permission layer
dylanroscoverllms.txtdylanroscover/Embody/web/llms-full.txt
bloom on the final output. ``` You're not getting a screenshot or a code snippet to paste. You're getting the **actual network**, in front of you, ready to play
garagonllms.txtgaragon/nanostack/llms.txt
work. Not a saved phase; the artifact appears on review. - /review: Two-pass code review (structural + adversarial). Detects scope drift against the plan and conflict-precedence against prior /security. - /security
nikolai-vysotskyiReads credentialsllms.txtnikolai-vysotskyi/trace-mcp/docs/llms-full.txt
requires external binaries and complex backend choices. [trace-mcp vs CodeGraphContext](/vs/codegraphcontext.html) | | **Review graph** | [code-review-graph](https://github.com/code-review-graph/code-review-graph) | Tracks incremental changes with empty-result uncertainty explanations. | Specialised
nikolai-vysotskyillms.txtnikolai-vysotskyi/trace-mcp/docs/llms.txt
calls return vs making structural questions about code cheap to ask. - [trace-mcp vs code-review-graph](https://trace-mcp.com/vs/code-review-graph.html): Head-to-head against the incremental SQLite graph peer — blast
wesmllms.txtwesm/middleman/docs/llms.txt
review, stacks, and merging - [Browse repositories](https://forge.kenn.io/docs/workflows/repositories.md): Repository source browser, refs, previews, and file history - [Work in local sessions](https://forge.kenn.io/docs/workflows/workspaces.md): Worktree workspaces, tmux sessions, and coding
tmseidelllms.txttmseidel/ai-git-bot/llms-full.txt
shared setup (workflow configurations, triggers, running workflows). - `doc/PR_WORKFLOWS_REVIEW.md`: the default always-on AI code review workflow. - `doc/PR_WORKFLOWS_AGENTIC_REVIEW.md`: deeper agentic PR review workflow. - `doc/PR_WORKFLOWS_UNIT_TEST.md`: AI unit-test workflow, supported toolchains, slash
tmseidelllms.txttmseidel/ai-git-bot/llms.txt
/tmseidel/ai-git-bot Docker image: https://hub.docker.com/r/tmseidel/ai-git-bot License: MIT ## Core capabilities - AI-powered pull-request code reviews triggered by reviewer assignment or re-request. - Interactive PR and inline review conversations with
willynikes2Reads credentialsllms.txtwillynikes2/knowledge-base-server/llms.txt
src/safety/review.js | Destructive action review with multi-model consensus. | | src/promotion/promoter.js | Knowledge promotion from sources to structured notes. | | src/synthesis/weekly-review.js | Weekly cross-source synthesis generator. | ## Integration Patterns ### Claude Code (local, stdio) Register with
paolobietolinillms.txtpaolobietolini/gtm-mcp-server/llms.txt
template details including .tpl code | | `create_template` | Create a custom template from .tpl code | | `update_template` | Modify an existing template | | `delete_template` | Remove a template (requires `confirm: true`) | | `import_gallery
arronKlerPipes a download into a shellllms.txtarronKler/pairfob/site/llms.txt
Sessions run in Herdr, which the installer sets up automatically. Pair once by QR code; no phone app required, no Pairfob account, no VPN, no inbound ports. An optional sideloaded
ihuzaifashoukatllms.txtihuzaifashoukat/x-use/llms.txt
bounded thread reads; structured notifications; visible inbox and conversation reads; local leads and campaigns; reviewed messages, follows, and multi-post threads. - Inbox folders are inbox, requests and other. All/unread/read filters
kestra-iollms.txtkestra-io/docs/public/llms.txt
environments directly from the Kestra UI with a diff review and confirmation gate — no Git or pipeline required - [VS Code extension](https://kestra.io/docs/version-control-cicd/vscode.md): Edit flows in VS Code with
softsparkReads credentialsllms.txtsoftspark/ai-toolkit/llms-full.txt
diffs for regression risk and blast radius, generates risk-scored impact report. Triggers: PR review, code change risk, breaking change, blast radius, regression check. - **prepare-test-env**: Prepare or verify
softsparkllms.txtsoftspark/ai-toolkit/llms.txt
kb/howto/autonomous-development.md) - [Claude Code Account Profiles by Project](kb/howto/claude-account-profiles.md) - [Codex account profiles](kb/howto/codex-account-profiles.md) - [Plan: Cloud Security Pack — Multi-Cloud Audit](kb/planning/cloud-security-pack-plan.md) - [Ecosystem sync, 2026-09-23](kb/planning/ecosystem-sync-20260923.md) - [Ecosystem review
tubecreatellms.txttubecreate/tubecli/docs/llms.txt
with no API key. Representative operations, all executed by agents rather than suggested as code: describe a site in plain language and the website agent runs `git clone` → `npm install
A markdown file at a website's root that gives language models a short guide to the site and links to the pages worth reading.
The same idea with the content included, so an agent can read the documentation in one request.
Agents and tools that fetch documentation on someone's behalf. It's a proposal, not a standard, and support varies.
Start with a one-line summary, then sections of links with a sentence each. The examples here show what real projects do.
