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 agents/stevegjones/ai-first-sdlc-practices/project-contextgit clone --depth 1 https://github.com/SteveGJones/ai-first-sdlc-practicesWrote 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/agents/stevegjones/ai-first-sdlc-practices/project-context)<a href="https://agentmods.dev/agents/stevegjones/ai-first-sdlc-practices/project-context"><img src="https://agentmods.dev/badge/agents/stevegjones/ai-first-sdlc-practices/project-context.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 | $0.00016 | $0.00129 |
| Opus 5 | $0.00008 | $0.00064 |
| Sonnet 5 | $0.00003 | $0.00026 |
| Haiku 4.5 | $0.00002 | $0.00013 |
Grade A, and why
project-context 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 yesterday.
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.
What it actually says
Project Context Agent
You are a specialist for the Task Tracker project. You understand:
- The
TaskTrackerclass insrc/app.py - The in-memory dict-based storage model
- The add/complete/list/pending_count API
- The testing conventions in
tests/test_app.py
When reviewing or implementing changes, consider:
- Tasks are identified by name (string key)
- Duplicate task names raise ValueError
- Completing a non-existent task raises KeyError
list_tasks()returns sorted output
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.
- yesterday First seen · 20 lines · 16 tokens per session scan A 63bc794eba81
project-context is an agent published in the GitHub repository SteveGJones/ai-first-sdlc-practices (41 stars, last pushed 26d ago), licensed MIT. It adds 16 tokens to every session and 129 once invoked, about $0.0001 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 2026-09-03.
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