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/claude-mdgit clone --depth 1 https://github.com/lbj96347/competeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/lbj96347/compete/claude-md)<a href="https://agentmods.dev/instructions/lbj96347/compete/claude-md"><img src="https://agentmods.dev/badge/instructions/lbj96347/compete/claude-md.svg" alt="Measured on agentmods" height="20"></a>What 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 | $0.01470 | $0.01470 |
| Opus 5 | $0.00735 | $0.00735 |
| Sonnet 5 | $0.00294 | $0.00294 |
| Haiku 4.5 | $0.00147 | $0.00147 |
Grade A, and why
compete CLAUDE.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 3d 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
What this is
compete is itself a Claude Code Skill (skills/compete/SKILL.md at the root), not a
conventional app. It turns the repository Claude is invoked in into a competitive
intelligence report. The deliverables are: Python helper scripts (stdlib only), JSON
Schemas, reference docs, and a self-contained HTML report template. There is no
package manager, build system, or test framework — just python and a browser.
When the skill runs, Claude itself is part of the pipeline: the scripts emit
research plans, Claude executes them with WebSearch/WebFetch, and the scripts
normalize Claude's findings back into schema-valid JSON.
Commands
Requirements: Python 3.9+ (stdlib only; jsonschema/referencing optional — scripts
fall back to built-in structural checks when absent).
The pipeline runs in five stages. The two middle stages are two-phase (plan →
Claude does web research → build):
# 1. Product Intelligence — repo → product.json
python skills/compete/scripts/analyze_repo.py --repo . --validate
# 2. Competitor Discovery (two-phase)
python skills/compete/scripts/discover_competitors.py plan --product product.json # → research plan (stdout)
# ...Claude runs the plan with WebSearch/WebFetch → candidates.json...
python skills/compete/scripts/discover_competitors.py build --product product.json \
--candidates candidates.json --validate # → competitors.json
# 3. Intelligence Collection (two-phase)
python skills/compete/scripts/collect_intelligence.py plan --competitors competitors.json
# ...Claude runs the plan → findings.json...
python skills/compete/scripts/collect_intelligence.py build --competitors competitors.json \
--findings findings.json --validate # → companies/pricing/techstack/social/marketing/seo.json
# 4 + 5. Knowledge Graph + Report — all datasets → report.json + report.html
python skills/compete/scripts/build_report.py --input-dir . --output-dir ./insightkit-output --open
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.
- 3d ago First seen · 106 lines · 1,470 tokens per session scan A 1b2d1812d553
compete CLAUDE.md is an instructions file published in the GitHub repository lbj96347/compete (9 stars, last pushed 2mo ago), licensed MIT. It adds 1,470 tokens to every session, about $0.0073 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.
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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.
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.