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/bmbouter/redhat-agents/feature-spec-writernpx skills add bmbouter/redhat-agents --skill feature-spec-writergit clone --depth 1 https://github.com/bmbouter/redhat-agentsWrote 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/bmbouter/redhat-agents/feature-spec-writer)<a href="https://agentmods.dev/skills/bmbouter/redhat-agents/feature-spec-writer"><img src="https://agentmods.dev/badge/skills/bmbouter/redhat-agents/feature-spec-writer.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 | $0.00027 | $0.00483 |
| Opus 5 | $0.00014 | $0.00242 |
| Sonnet 5 | $0.00005 | $0.00097 |
| Haiku 4.5 | $0.00003 | $0.00048 |
Grade A, and why
feature-spec-writer 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 4d 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.
What it actually says
When to Use
When the PM has a feature idea, customer request, or stakeholder conversation that needs to be turned into a formal spec.
Instructions
Read local/jira-workflow.md to understand the epic description template and field conventions.
1. Gather input
Ask the PM for the raw input — this could be:
- Conversation notes or meeting minutes
- A customer request or support escalation
- A Slack thread or email
- A verbal description of what they want
2. Ask clarifying questions
Before writing, make sure you understand:
- Who has this problem? (customer segment, persona)
- What is the problem? (not the solution — the underlying need)
- Why does it matter? (business impact, strategic alignment)
- What does success look like? (measurable outcomes)
- What's out of scope? (boundaries)
3. Draft the spec
Use the epic description template from the workflow config. If none exists, use this structure:
h2. Functionality Overview
[High-level description of what this feature delivers]
h2. Problem Statement
[The specific customer/market problem this addresses]
h2. Goals
* [Goal 1 — measurable outcome]
* [Goal 2]
h2. Requirements
||Requirement||Notes||isMvp||
|[Requirement 1]|[Notes]|yes/no|
|[Requirement 2]|[Notes]|yes/no|
h2. Use Cases
* [Use case 1 — who does what and why]
* [Use case 2]
h2. Out of Scope
* [What is explicitly NOT included]
h2. Background and Strategic Fit
[Why this matters strategically]
h2. Assumptions
* [Key assumption 1]
* [Key assumption 2]
h2. Open Questions
|Question|Outcome|
|[Open question 1]|[Answer when resolved]|
4. Review and iterate
Present the spec to the PM. Iterate based on feedback. Once approved, offer to create the epic in Jira with the spec as the description.
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.
- 4d ago First seen · 82 lines · 27 tokens per session scan A 47a4acff0486
feature-spec-writer is a skill published in the GitHub repository bmbouter/redhat-agents (5 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 27 tokens to every session and 483 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 2026-08-31.
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