Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/lbj96347/compete/agents-mdgit clone --depth 1 https://github.com/lbj96347/competeWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00586 | $0.00586 |
| Opus 5 | $0.00293 | $0.00293 |
| Sonnet 5 | $0.00117 | $0.00117 |
| Haiku 4.5 | $0.00059 | $0.00059 |
Grade A, and why
compete AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 38 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repository Guidelines
Project Structure & Module Organization
This repository is a Claude Code Skill for competitive intelligence. skills/compete/SKILL.md defines triggers and workflow, while PRD.md and skills/compete/references/ describe the product scope and stage-specific rules. Python pipeline helpers live in skills/compete/scripts/: analyze_repo.py, discover_competitors.py, collect_intelligence.py, and build_report.py. JSON datasets at the repo root, such as product.json, competitors.json, and pricing.json, are the normalized data contract. Schemas are in skills/compete/schemas/, and the report UI template is skills/compete/templates/report.html.
Build, Test, and Development Commands
Use Python 3.9+; the scripts rely on the standard library, with optional jsonschema support.
python skills/compete/scripts/analyze_repo.py --repo . --validate
Analyzes this repository and validates product.json.
python skills/compete/scripts/build_report.py --input-dir . --output-dir ./insightkit-output
Builds report.json and the standalone report.html output. Use --open only when you want the script to launch a browser.
Coding Style & Naming Conventions
Follow the existing Python style: 4-space indentation, type hints where useful, small deterministic helpers, and explicit docstrings for pipeline entry points. Keep file names and dataset names lowercase with underscores where needed. Preserve the confidence-envelope pattern for collected values: include value, confidence, unknown, source, and provenance; when unknown is true, value must be null.
Testing Guidelines
There is no separate test suite currently. Validation is schema-driven, so run the relevant script with --validate after changing data extraction, normalization, or schemas. If you touch skills/compete/templates/report.html, skills/compete/schemas/, or skills/compete/scripts/build_report.py, regenerate insightkit-output/ and inspect the rendered report in a browser.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 38 lines · 586 tokens per session scan A ca7ecfc09c29
compete AGENTS.md is an instructions file published in the GitHub repository lbj96347/compete (9 stars, last pushed 2mo ago), licensed MIT. It adds 586 tokens to every session, about $0.0029 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other instructions, from other repositories
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
next.js AGENTS.md
Instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.