How real projects summarise themselves for language models.
benseverndev-ossllms.txtbenseverndev-oss/goldenmatch/llms.txt
config gets good results and returns the config it chose; the healer (`review_config`) reviews those results and suggests ranked, self-verified tweaks; you apply them, results improve, repeat
poemswellms.txtpoemswe/co-researcher/llms-full.txt
selective coding; codebook development - Thematic analysis: theme identification, saturation assessment, negative case analysis - Reflexivity: prompts researcher positionality documentation - Output: codebook, theme map, saturation assessment, reflexivity memo ### Peer Review (`/review`) Structures
poemswellms.txtpoemswe/co-researcher/llms.txt
effect size interpretation, Simpson's paradox detection - **Qualitative Research** — thematic analysis, coding strategy, leading-question detection - **Peer Review** — manuscript critique and methodological rigor scoring - **Ethics Review** — IRB compliance, privacy risk
sandbaseaillms.txtsandbaseai/deepseek-harness-handbook/site/llms.txt
public dsh-plugin topic repositories + 471 manual additions); this handbook intentionally exposes a reviewed subset: https://github.com/0xsline/awesome-deepseek-harness/blob/07278233cba25e6f2d011018751187b7a4d8ed52/CATALOG.md SandBase Harness MCP bridge guide: https://sandbaseai.github.io/deepseek-harness-handbook/sandbase-harness-bridge.html English README and Star
X-isdoingreatllms.txtX-isdoingreat/canvas-pilot/site/llms.txt
open source" -> Canvas Pilot automates recurring assignment workflows while keeping review and submission under student control. - "Canvas LMS Claude Code Codex agent" -> Canvas Pilot supports the local-agent workflow shape
Houseofmvpsllms.txtHouseofmvps/ultraship/llms.txt
spec approval, step-by-step implementation plans, test-driven development, systematic debugging, AI-powered code review, and a pre-deploy quality gate that scans SEO, security, performance, code quality
VKirillllms.txtVKirill/claude-lane-stack/llms.txt
database or cloud service — plain files + plain git. MIT license. Key facts: - Only Claude Code is required; workers optional and auto-detected by `agents-doctor` (profiles: full → claude-only). - Task
agents-uillms.txtagents-ui/agents-kit/llms-full.txt
local notes, and switch voice mode on when useful | `example-chat-app` | | Coding workspace | Select files, review a proposed patch, accept or reject changes, and run checks against the accepted
agents-uillms.txtagents-ui/agents-kit/llms.txt
then switch to voice without losing your draft. - [example-coding-app](https://agents-ui.github.io/agents-kit/c/example-coding-app.json): An agent proposes a patch, you review it, and the checks explain the result. - [example-voice
hermes-labs-aillms.txthermes-labs-ai/lintlang/llms-full.txt
format gitlab > gl-code-quality-report.json lintlang scan config.yaml --fail-on fail lintlang scan config.yaml --fail-on review lintlang scan config.yaml --min-severity high lintlang scan config.yaml --patterns H1 H3 lintlang scan prompts
Kilbexllms.txtKilbex/Vigla/llms.txt
Revert the whole mission when the result is wrong. --- Five coding agents should not mean five terminals, five diff reviews, and five unread merges. Vigla gives the work one operations
EliasOulkadillms.txtEliasOulkadi/shokunin/llms.txt
Mobile**: flutter, react-native - **Quality**: test-commander, performance-profiler, code-review - **Content**: content-marketing, translate-craft, communication, documentation - **Productivity**: git-workflow, windows-powershell, strategy, finance - **Documents**: kami, kagen, portfolio-auto
EliasOulkadillms.txtEliasOulkadi/shokunin/.pack/llms.txt
Mobile**: flutter, react-native - **Quality**: test-commander, performance-profiler, code-review - **Content**: content-marketing, translate-craft, communication, documentation - **Productivity**: git-workflow, windows-powershell, strategy, finance - **Documents**: kami, kagen, portfolio-auto
kagan-shllms.txtkagan-sh/kagan-legacy/docs/llms.txt
Kagan Documentation > Documentation for Kagan: a Kanban TUI for AI coding agents with a structural human review gate. No agent-authored task reaches your main branch without an explicit approval
hogancvllms.txthogancv/coordinate-agents/docs/llms.txt
Task Skill: https://github.com/hogancv/coordinate-agents/blob/main/skills/coordinate-task/SKILL.md Review Skill: https://github.com/hogancv/coordinate-agents/blob/main/skills/coordinate-review/SKILL.md Recovery Skill: https://github.com/hogancv/coordinate-agents/blob/main/skills/coordinate-recover/SKILL.md Plugin-first onboarding: Install the Plugin, Discover local coding CLIs with `coordinate_agents_setup_discover
xhlucallms.txtxhluca/session-migrate/llms.txt
session-migrate`. Use `"$TMP/venv/bin/session-migrate"` for every operation and verify its version. Do not run code from an untrusted fork. If installation or version verification fails, stop; never reproduce or infer
Apra-Labsllms.txtApra-Labs/apra-fleet/llms.txt
doer-reviewer loop. - [Troubleshooting](docs/troubleshooting.md): Common symptoms and fixes. ## Project - [Roadmap](ROADMAP.md): What is planned next for Apra Fleet. - [Contributing](CONTRIBUTING.md): How to contribute code, docs, and skills. ## Community - [GitHub
0xzrllms.txt0xzr/freellmpool/docs/llms.txt
speaks the OpenAI API and has an experimental Anthropic-compatible path, > so Codex, Claude Code, and aider run on pooled free models unchanged. MIT licensed. > Capacity tools (`freellmpool capacity status
dykyi-romanllms.txtdykyi-roman/awesome-claude-code/llms.txt
/acc:generate-test ` | Generate tests for file/folder | | `/acc:audit-test ` | Audit test quality | | `/acc:code-review [branch] [level]` | Multi-level code review | | `/acc:bug-fix ` | Automated bug diagnosis
2389-researchllms.txt2389-research/claude-plugins/docs/llms.txt
Linux, Windows, and macOS without Xcode - [speed-run](https://skills.2389.ai/plugins/speed-run/): Token-efficient code generation pipeline - parallel implementation with hosted LLM (Cerebras) for ~60% token savings. Includes MCP server. - [binary
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.
