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 genkovich/sdd --skill reviewgit clone --depth 1 https://github.com/genkovich/sddWrote 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/genkovich/sdd/review)<a href="https://agentmods.dev/skills/genkovich/sdd/review"><img src="https://agentmods.dev/badge/skills/genkovich/sdd/review.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00140 | $0.01916 |
| Opus 5 | $0.00070 | $0.00958 |
| Sonnet 5 | $0.00028 | $0.00383 |
| Haiku 4.5 | $0.00014 | $0.00192 |
Grade A, and why
review 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 7d 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 — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: review
The independent review gate. After implement has written + tested + committed the code, review looks at the whole change at once, with fresh eyes — does it actually satisfy every acceptance criterion, and is it good code? This is distinct from the per-task gate inside implement (which proves each task green): review is the cross-cutting, clean-context pass a human reviewer would do on the PR.
It reuses the shared clean-context discipline (../_shared/critic.md) and the reviewer subagent (read-only). Question phrasing per ../_shared/ask-style.md.
Review-record prose follows artifact_language (carry the language in the reviewer's dispatch prompt) — the verdict literals PASS / CHANGES REQUESTED / REVIEW_CLEAN and cited identifiers stay English → ../_shared/artifact-language.md.
Owner
Tech Lead / a reviewer who did not write the code (independence is the point).
Inputs
<slug>— feature slug.- Gate (hard refuse): an implemented change must exist (commits on the feature branch, or a non-empty working diff). Nothing to review → «run
implement <slug>first». - Read for the review baseline — the whole AC chain, so the trace can be checked end-to-end:
docs/features/<slug>/spec.md§5 (the full AC set — the source of truth, not the diff's trailers),sad.md§6 (the sequence flows/branches each AC should appear in),data-model.md/contracts/openapi.yaml/ Acceptedadr/(the contracts the code must honour),test-plan.md(the AC→test map, if a separate file), andtasks.json(which AC each task claimed).
Protocol
- Scope the diff. Determine the change under review:
git diff <base>..HEADon the feature branch (base = the branch point), or the named changed files. Note theSDD-ACtrailers — the ACs the implementation claims to satisfy. - Dispatch the independent reviewer. Run the
revieweragent —subagent_type: "sdd:reviewer"(read-only, clean context — it re-reads spec/contracts itself, no paraphrase; model perjudgment_model; effortxhighon L/XL viaCLAUDE_CODE_EFFORT_LEVEL, per../_shared/agent-roster.md) — over the diff along the dimensions in./references/review-dimensions.md: stage 1 — every claimed AC genuinely satisfied and the whole §4 user-story set + §5 AC set traced end-to-end (spec → sequences §6 → data-model → api → tasks → implement): every §4 user story has ≥1 AC and a §6 flow, and every §5 AC reaches code+test — spanning every surface declared insad.mdtarget_surfaces(a UI AC traces to a component / e2e-through-UI test, not only a backend one) — flagging any user story or AC that dropped out anywhere in the chain, not only the ACs the diff claims via itsSDD-ACtrailers; stage 2 — conventions, error/edge handling, security, boundary violations, test adequacy. For a large diff, fan out one reviewer per dimension and merge. - Collect cited findings. Each finding cites
file:line+ the AC/contract it touches. Drop uncited findings (per the critic discipline). A clean review returnsREVIEW_CLEAN. If the reviewer ran asynchronously and came back as an idle/completion signal with no report, pull the full report through the host's messaging channel — never accept a verdict without its text (→../_shared/agent-roster.md, shared-contract point 2). - Resolve each finding with the user via
AskUserQuestion: Fix now (hand the actionable finding back toimplement/the author as a follow-up task — re-enter the TDD loop for it) / Defer (record in spec §8 Open questions with owner + due) / Not an issue (the reviewer misread; record why). Never ship an unresolved stage-1 (AC) finding. - Write the review record.
docs/features/<slug>/_review/review-<date>.md: scope (diff stat), findings with verdicts, and the gate result (PASS/CHANGES REQUESTED). - Verdict + next. Then emit the stage-handoff block per
../_shared/handoff.md— What I did + Review (_review/review-<date>.md) + Run next:PASS→ (/clear, then/sdd:ship <slug>);CHANGES REQUESTED→/sdd:implement <slug>for the fixes (no/clear— stay in context to iterate), then re-review the changed surface.
What ships with it
1 file 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.
- 7d ago First seen · 64 lines · 140 tokens per session scan A 5f09a4b781db
review is a skill published in the GitHub repository genkovich/sdd (133 stars, last pushed 2d ago), licensed MIT. It adds 140 tokens to every session and 1,916 once invoked, about $0.0007 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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