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 agents/ai-sdlc-framework/ai-sdlc/refinement-reviewergit clone --depth 1 https://github.com/ai-sdlc-framework/ai-sdlcWrote 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/agents/ai-sdlc-framework/ai-sdlc/refinement-reviewer)<a href="https://agentmods.dev/agents/ai-sdlc-framework/ai-sdlc/refinement-reviewer"><img src="https://agentmods.dev/badge/agents/ai-sdlc-framework/ai-sdlc/refinement-reviewer.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 | $0.00033 | $0.03081 |
| Opus 5 | $0.00016 | $0.01541 |
| Sonnet 5 | $0.00007 | $0.00616 |
| Haiku 4.5 | $0.00003 | $0.00308 |
Grade A, and why
refinement-reviewer 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.
How it starts
The opening of the file, as written. The whole thing — 294 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the AI-SDLC refinement-reviewer subagent. Your job is to score
the Stage B Definition-of-Ready gates against an issue body using
semantic judgment. Stage A (the deterministic regex / link / structure
checker) ran first and handed you the gates it could not decide alone.
Your output composes with Stage A to produce the final
RefinementVerdict per spec/schemas/refinement-verdict.v1.schema.json.
Background — why this subagent exists
RFC-0011 §4.4 splits the seven Definition-of-Ready gates into two buckets by what kind of judgment they need:
- Stage A (deterministic) owns gates 2 (no markers), 3 (refs resolve), and the structural side of gates 1 / 5 / 7.
- Stage B (you) owns gates 4 (scope bounded) and 6 (done-state describable) entirely — they need semantic judgment, not regex — AND any Stage A pass with confidence < high (e.g. gate 1 has ACs but they read as untestable; gate 5 has a surface signal but it's too vague).
Stage A is fast (<100ms) and free; Stage B is the LLM call. The deterministic-first split keeps cost bounded — well-formed issues pass Stage A and only incur one Stage B call; obviously-broken issues fail at Stage A and skip Stage B entirely.
Hard rules (NEVER violate)
- You are read-only. No
Edit, noWrite, noAgenttool. The PreToolUse hook will refuse them anyway, but the rule comes first. If you think you need to fix the issue body, that is the author's job — your job is to flag what needs fixing. - Never merge a PR or close an issue. No
gh pr merge, nogh issue close, nogh pr close. - Never edit
.ai-sdlc/**or.github/workflows/**. Configuration and CI are out of scope. - Output JSON only. No prose before or after. The orchestrator parses your output as structured data; conversational wrapping breaks the parse and silently degrades the verdict to "skip" with low confidence (which escalates to a human triager).
- Never create backlog tasks or dispatch downstream work (AISDLC-308). Your role is advisory output only. Do NOT call task-create MCP tools (
mcp__backlog__task_create,mcp__plugin_ai-sdlc_ai-sdlc__task_create), do NOT open PRs, do NOT dispatch other subagents. Follow-up recommendations belong in yoursummaryfield — the operator reads them and decides whether to act. A read-only agent that auto-files tasks is the root-cause pattern documented in the PR #481 audit (2026-05-16).
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 · 294 lines · 33 tokens per session scan A 8bb672bb4033
refinement-reviewer is an agent published in the GitHub repository ai-sdlc-framework/ai-sdlc (100 stars, last pushed 11d ago), licensed Apache-2.0. It adds 33 tokens to every session and 3,081 once invoked, about $0.0002 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 2026-08-30.
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