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 skills/bsahane/memory-mcp-server/bmad-project-contextnpx skills add bsahane/memory-mcp-server --skill bmad-project-contextgit clone --depth 1 https://github.com/bsahane/memory-mcp-serverWrote 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/skills/bsahane/memory-mcp-server/bmad-project-context)<a href="https://agentmods.dev/skills/bsahane/memory-mcp-server/bmad-project-context"><img src="https://agentmods.dev/badge/skills/bsahane/memory-mcp-server/bmad-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 5.1 | $0.00049 | $0.01853 |
| Opus 5 | $0.00024 | $0.00927 |
| Sonnet 5 | $0.00010 | $0.00371 |
| Haiku 4.5 | $0.00005 | $0.00185 |
Grade A, and why
bmad-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 5d 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.
This is a copy
100% identical to bmad-project-context — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Overview
A conversation that produces a repository's agent instructions: a small verified block inside AGENTS.md. The user brings rules they want followed — governance, security, standards — and the repository supplies the rest, verified.
Conversational always; the user approves every write.
Args: intent (setup | refresh | record | audit); a target repo or path; extra source paths or URLs. Supplied values skip their questions.
Resolution rules
- Bare paths and
{skill-root}(e.g.references/best-practices.md) resolve from this skill's installed directory. {project-root}→ the project working directory.- Target → the repository being described, defaulting to
{project-root}. If it resolves to more than one working tree, or to one the user cannot commit in, ask before writing.
On Activation
- Resolve customization:
uv run {project-root}/_bmad/scripts/resolve_customization.py --skill {skill-root} --key workflow. On failure, read{skill-root}/customize.tomldirectly and use defaults. Execute{workflow.activation_steps_prepend}; treat{workflow.persistent_facts}entries as standing context (file:= paths/globs to load, others verbatim). - Config: if
{project-root}/_bmadexists,uv run {project-root}/_bmad/scripts/resolve_config.py --project-root {project-root}and read{user_name},{communication_language}(use it every turn),{output_folder}. Standalone: skip. - Load
references/best-practices.mdandreferences/template.mdbefore anything else. Every decision below is made against them. - Detect intent and greet
{user_name}: setup (no block in the target — the default), refresh (a block exists), record (the user reports a mistake agents made), audit (re-verify and prune). Fold{workflow.external_sources}into the source list. Execute{workflow.activation_steps_append}.
Setup and Refresh Steps
No writes until step 5!
1. Assess and report
Read AGENTS.md, harness or agent specific rule files, docs folders, and any notes carrying lessons. Report what exists and how it measures up, per best-practices.md.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 5d ago First seen · 111 lines · 49 tokens per session scan A 1a276f306ed7
bmad-project-context is a skill published in the GitHub repository bsahane/memory-mcp-server (0 stars, last pushed 14d ago), licensed Apache-2.0. It adds 49 tokens to every session and 1,853 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to bmad-project-context, differing in 0 lines, and is treated as a copy.
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