Borrowing it
Nothing to install: this file belongs to OlliMakarova/mcp-metro. 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/OlliMakarova/mcp-metro/master/.claude/skills/feature-prompt-generator/SKILL.mdgit clone --depth 1 https://github.com/OlliMakarova/mcp-metroWrote 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/ollimakarova/mcp-metro/feature-prompt-generator)<a href="https://agentmods.dev/skills/ollimakarova/mcp-metro/feature-prompt-generator"><img src="https://agentmods.dev/badge/skills/ollimakarova/mcp-metro/feature-prompt-generator/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/ollimakarova/mcp-metro/feature-prompt-generator"><img src="https://agentmods.dev/badge/skills/ollimakarova/mcp-metro/feature-prompt-generator.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 | $0.00094 | $0.04638 |
| Opus 5.5 | $0.00038 | $0.01855 |
| Sonnet 5.5 | $0.00019 | $0.00928 |
| Haiku 4.5 | $0.00009 | $0.00464 |
Grade A, and why
feature-prompt-generator scanned grade A with 1 finding 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 2mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
allowed-tools: Read, Grep, Glob, Bash(git *), Bash(yarn *), Bash(npm *), Bash(node *), Bash(ls *), Bash(cat *), Bash(curl *), WebFetch, WebSearch, mcp__context7__resolve-library-id, mcp__context7__query-docs How it starts
The opening of the file, as written. The whole thing — 381 lines — stays where its author put it; the contents beside it link to each section on GitHub.
feature-prompt-generator — META-SKILL for generating prompts for an AI CLI
Essence
You do NOT write code. You generate a self-sufficient prompt for an AI CLI, which will then:
- study the code itself,
- design the solution itself,
- implement it itself,
- test it itself.
This is a META-skill (agent-building agent). Your output is a clean prompt, not an implementation. You do not touch any code in the target repository.
How to invoke
Command-only. The skill is never auto-invoked by the model — disable-model-invocation
is set to true. Runs solely when the operator explicitly calls it (e.g. /feature-prompt-generator
or the equivalent UI invocation). Ignore any implicit triggers from phrasing in user messages.
When to use
- The operator describes a feature/functionality but does not write code themselves.
- A production-ready prompt is needed to hand off to Claude Code / another AI agent.
Method — shared with the other skills
How you think, and how you study a source of truth, is defined once — in
${CLAUDE_SKILL_DIR}/../_shared/source-research.md. Read that file before STEP 1 and follow it for
the whole run. It carries the seven core principles (think before code, simplicity first, surgical
changes, goal-driven steps, anti-hallucination, surfaced assumptions, ask rather than guess), the
classification of source kinds, the baseline project reads, the inventory each kind of source demands,
the rules for mapping a source's operations onto an MCP surface, and the hard prohibitions.
The shape of the document you produce is defined once as well — in
${CLAUDE_SKILL_DIR}/../_shared/prompt-plan-format.md. Part B of your output is a prompt-plan and
obeys that format. Read it before writing Part B.
Neither file is optional, and neither is summarized into the output: this skill adds only what is specific to turning research into a hand-off prompt.
Input
The operator passes via $ARGUMENTS:
- a free-form feature description, OR
- a path to a file with the description (
task.md, issue dump from a tracker, dialog excerpt).
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.
- 2mo ago First seen · 381 lines · 94 tokens per session scan A f647d0fc2837
feature-prompt-generator is a skill published in the GitHub repository OlliMakarova/mcp-metro (0 stars, last pushed 3mo ago), licensed MIT. It adds 94 tokens to every session and 4,638 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
feature-prompt-generator compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| feature-prompt-generatorOlliMakarova/mcp-metro | Skill | 0 | 3mo ago | MIT | A | 94 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |