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/vintasoftware/django-ai-boost/agents-mdgit clone --depth 1 https://github.com/vintasoftware/django-ai-boostWrote 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/vintasoftware/django-ai-boost/agents-md)<a href="https://agentmods.dev/instructions/vintasoftware/django-ai-boost/agents-md"><img src="https://agentmods.dev/badge/instructions/vintasoftware/django-ai-boost/agents-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 | $0.01429 | $0.01429 |
| Opus 5 | $0.00714 | $0.00714 |
| Sonnet 5 | $0.00286 | $0.00286 |
| Haiku 4.5 | $0.00143 | $0.00143 |
Grade A, and why
django-ai-boost 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 4d 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Guidance for coding agents working in django-ai-boost.
1) Project Snapshot
- Python package:
django-ai-boost - Purpose: MCP server exposing read-only Django introspection tools
- Runtime: Python
>=3.12 - Core deps:
django>=4.2,fastmcp>=3.2.4 - Package manager:
uv - Entry point:
django-ai-boost->django_ai_boost:main - Main server module:
src/django_ai_boost/server_fastmcp.py
2) Environment Setup
- Install runtime deps:
uv sync
- Install dev deps:
uv sync --dev
- Verify CLI:
uv run django-ai-boost --help
3) Build / Lint / Format Commands
- Lint all Python files:
uv run ruff check .
- Auto-fix lint issues:
uv run ruff check --fix .
- Format code:
uv run ruff format .Notes:
- There is no separate compile/build step for this repository.
ruffis the formatter and linter source of truth.
4) Test Commands
Pytest is the default test runner in this repo:
- Run all tests:
uv run pytest
- Verbose mode:
uv run pytest -v
- Focus on migrated MCP tool tests:
uv run pytest test_auth_logic.py test_prompt.py test_query_model.py test_read_recent_logs.py test_run_check.py
- Run broad integration coverage:
uv run pytest test_server.py
Running a single test (important)
Use one of these patterns:
- Single pytest file:
uv run pytest test_auth_logic.py
- Single pytest test function:
uv run pytest test_auth_logic.py::test_validation_logic
- Filter by test name substring:
uv run pytest -k validation_logic
5) Running the Server Locally
With env var:
export DJANGO_SETTINGS_MODULE=myproject.settingsuv run django-ai-boostWith explicit settings arg:uv run django-ai-boost --settings myproject.settingsSSE transport:uv run django-ai-boost --settings myproject.settings --transport sseuv run django-ai-boost --settings myproject.settings --transport sse --host 127.0.0.1 --port 8000Fixture project quick run:export PYTHONPATH="${PYTHONPATH}:./fixtures/testproject"uv run django-ai-boost --settings testproject.settings
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.
- 4d ago First seen · 141 lines · 1,429 tokens per session scan A 8f294cd9b379
django-ai-boost AGENTS.md is an instructions file published in the GitHub repository vintasoftware/django-ai-boost (111 stars, last pushed 1mo ago), licensed MIT. It adds 1,429 tokens to every session, about $0.0071 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 2026-08-30.
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blockrun-mcp AGENTS.md
AGENTS.md instructions for BlockRunAI/blockrun-mcp, covering blockrun mcp, commands, project structure, key dependencies and install in codex.
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intervals-icu-mcp CLAUDE.md
Instructions for hhopke/intervals-icu-mcp, covering claude.md, project overview, development commands, architecture (quick reference) and tool categories.
ai-toolkit AGENTS.md
AGENTS.md instructions for pipefy/ai-toolkit, covering repository guidelines, documentation map, project structure, import namespace migration: pipefysdk → pipefy and src/pipefysdk/init.py (transitional shim).
flyto-core CLAUDE.md
Claude Code instructions for flytohub/flyto-core, covering claude notes, cross-agent handoff and shared code intelligence.