Borrowing it
Nothing to install: this file belongs to lailai258/agent-bridge-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/lailai258/agent-bridge-mcp/main/.agents/skills/bmad-customize/SKILL.mdgit clone --depth 1 https://github.com/lailai258/agent-bridge-mcpWrote 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/lailai258/agent-bridge-mcp/bmad-customize)<a href="https://agentmods.dev/skills/lailai258/agent-bridge-mcp/bmad-customize"><img src="https://agentmods.dev/badge/skills/lailai258/agent-bridge-mcp/bmad-customize/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/lailai258/agent-bridge-mcp/bmad-customize"><img src="https://agentmods.dev/badge/skills/lailai258/agent-bridge-mcp/bmad-customize.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00044 | $0.01613 |
| Opus 5 | $0.00022 | $0.00807 |
| Sonnet 5 | $0.00009 | $0.00323 |
| Haiku 4.5 | $0.00004 | $0.00161 |
Grade A, and why
bmad-customize 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 9d 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-customize — 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 — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BMad Customize
Translate the user's intent into a correctly-placed TOML override file under {project-root}/_bmad/custom/ for a customizable agent or workflow skill. Discover, route, author, write, verify.
Scope v1: per-skill [agent] overrides (bmad-agent-<role>.toml / .user.toml) and per-skill [workflow] overrides (bmad-<workflow>.toml / .user.toml). Central config ({project-root}/_bmad/custom/config.toml) is out of scope — point users at the How to Customize BMad guide.
When the target's customize.toml doesn't expose what the user wants, say so plainly. Don't invent fields.
Preflight
- No
{project-root}/_bmad/→ BMad isn't installed. Say so, stop. {project-root}/_bmad/scripts/resolve_customization.pymissing → continue, but Step 6 verify falls back to manual merge.- Both present → proceed.
Activation
Load _bmad/config.toml and _bmad/config.user.toml from {project-root} for user_name (default BMad) and communication_language (default English). Greet. If the user's invocation already names a target skill AND a specific change, jump to Step 3.
Step 1: Classify intent
- Directed — specific skill + specific change → Step 3.
- Exploratory — "what can I customize?" → Step 2.
- Audit/iterate — wants to review or change something already customized → Step 2, lead with skills that have existing overrides; read the existing override in Step 3 before composing.
- Cross-cutting — could live on multiple surfaces → Step 3, choose agent vs workflow explicitly with the user.
Step 2: Discovery
python3 {skill-root}/scripts/list_customizable_skills.py --project-root {project-root}
Use --extra-root <path> (repeatable) if the user has skills installed in additional locations.
Group the returned agents and workflows for the user; for each show name, description, whether has_team_override or has_user_override is true. Surface any errors[]. For audit/iterate intents, lead with already-overridden entries.
What ships with it
2 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.
- 9d ago First seen · 112 lines · 44 tokens per session scan A 7617ef46b179
bmad-customize is a skill published in the GitHub repository lailai258/agent-bridge-mcp (0 stars, last pushed 3mo ago), licensed MIT. It adds 44 tokens to every session and 1,613 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-customize, differing in 0 lines, and is treated as a copy.
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