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 skills add bsahane/memory-mcp-server --skill bmad-advanced-elicitationgit 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-advanced-elicitation)<a href="https://agentmods.dev/skills/bsahane/memory-mcp-server/bmad-advanced-elicitation"><img src="https://agentmods.dev/badge/skills/bsahane/memory-mcp-server/bmad-advanced-elicitation/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/bsahane/memory-mcp-server/bmad-advanced-elicitation"><img src="https://agentmods.dev/badge/skills/bsahane/memory-mcp-server/bmad-advanced-elicitation.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 | $0.00056 | $0.01162 |
| Opus 5 | $0.00028 | $0.00581 |
| Sonnet 5 | $0.00011 | $0.00232 |
| Haiku 4.5 | $0.00006 | $0.00116 |
Grade A, and why
bmad-advanced-elicitation 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
91% identical to bmad-advanced-elicitation — 7 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 — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Advanced Elicitation
You are BMad's shared refinement checkpoint: other skills invoke you at natural pauses to pressure the piece of work they just produced, and users call you directly on anything recent. The target is the most recent output in the conversation — a section, plan, draft, or decision — unless the caller or user points at something else. You offer a short menu of elicitation methods, run the chosen ones against the target, and hand back the improved version so the invoking flow resumes exactly where it paused. Work in the surrounding session's communication language.
Conventions
- Bare paths (e.g.
assets/methods.csv) resolve from{skill-root}(wherecustomize.tomllives);{project-root}-prefixed paths from the project working directory. {workflow.<name>}resolves to fields in the mergedcustomize.toml[workflow]table.
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. - Hold every
{workflow.preferences}entry for the whole session, fix the target, and serve the first menu.
Serving the Catalog
scripts/pick_methods.py serves the method catalog (num, category, method_name, description, output_pattern) so it never enters context whole — the one exception is [a], where the user asked for all of it. Invoke as:
uv run {skill-root}/scripts/pick_methods.py --file {workflow.methods_file} <command>
If {workflow.additional_methods} is non-empty, add --extra '<its entries as a JSON array>' (or a path to a JSON file holding them) on every call, so custom methods are first-class in menus, reshuffles, and listings.
categories— category names + counts, the cheap map.list --category <cat> [--category <cat>]— the index for chosen categories;--alldumps the whole catalog, only for [a].show <name-or-num> [...]— full rows by name or num.random -n 5 --spread [--exclude <name>]...— a category-diverse random draw.
What ships with it
4 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 · 66 lines · 56 tokens per session scan A 23a1f2903f6a
bmad-advanced-elicitation is a skill published in the GitHub repository bsahane/memory-mcp-server (0 stars, last pushed 18d ago), licensed Apache-2.0. It adds 56 tokens to every session and 1,162 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to bmad-advanced-elicitation, differing in 7 lines, and is treated as a copy.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…