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sdd-review

sdd-review is a skill for Claude Code from 3062-in-zamud/knowledgine. It costs 48 tokens per session (785 once invoked), scanned A, original, MIT.

A spec-compliance review tool that compares an implementation with its requirements, design, tasks, project rules, and review checklist. It produces pass, fail, or warning results.

In plain words
What is it for?
Use it after implementation and pull-request creation, before requesting review, or when checking someone else’s work against a specification.
Why use it?
It helps catch missing acceptance criteria, untested work, design mismatches, and violations of project standards before review.

Skill for Claude Code

Written for Claude Code: $ARGUMENTS substitution. Also seen: mentions Claude Code; mentions AGENTS.md; mentions Codex.

not rated 3repo 1mo ago A scan 48 tokens original MIT

Good fit Use it after implementation and pull-request creation, before requesting review, or when checking someone else’s work against a specification.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/3062-in-zamud/knowledgine/sdd-review
View source ↗ 3062-in-zamud/knowledgine
Install

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.

Any agent
npx skills add 3062-in-zamud/knowledgine --skill sdd-review
Clone the repo
git clone --depth 1 https://github.com/3062-in-zamud/knowledgine

Made for: Claude Code.

Wrote 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.

agentmods badge for sdd-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/3062-in-zamud/knowledgine/sdd-review/github.svg)](https://agentmods.dev/skills/3062-in-zamud/knowledgine/sdd-review)
Your own site
<a href="https://agentmods.dev/skills/3062-in-zamud/knowledgine/sdd-review"><img src="https://agentmods.dev/badge/skills/3062-in-zamud/knowledgine/sdd-review/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.

agentmods 80×15 button for sdd-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/3062-in-zamud/knowledgine/sdd-review"><img src="https://agentmods.dev/badge/skills/3062-in-zamud/knowledgine/sdd-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 48 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 785 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00048 $0.00785
Opus 5 $0.00024 $0.00392
Sonnet 5 $0.00010 $0.00157
Haiku 4.5 $0.00005 $0.00078

Measured 12d ago against content hash 55215af4e577, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

sdd-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 12d 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.

.ai-agents/skills/sdd-review/SKILL.md · 124 lines

How it starts

The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.

sdd-review

Purpose

Ensure implementation is complete, correct, and compliant with both the spec and project standards. This is the Claude Code counterpart to Codex's automated PR review.

When to Use

  • After implementation is complete and PR is created
  • As a pre-review self-check before requesting Codex review
  • When reviewing someone else's implementation against a spec

Arguments

  • $ARGUMENTS: Spec ID (e.g., KNOW-001) or PR number

Step-by-Step Instructions

1. Load Review Context

  1. Read the full spec: specs/KNOW-{NNN}-*/
  2. Read the review checklist: .ai-agents/config/review-checklist.md
  3. Read the diff (if PR number provided, use gh pr diff)
  4. Read AGENTS.md for project-level rules

2. Spec Compliance Check

For each acceptance criterion in requirements.md:

  • Verify a corresponding test exists
  • Verify the test passes
  • Verify the implementation actually satisfies the criterion (not just a superficial test)

For design.md:

  • Compare TypeScript interfaces in code vs design
  • Verify data flow implementation matches design
  • Check that design decisions were followed (not violated)

For tasks.md:

  • Verify all tasks are checked off
  • Identify any unplanned tasks that were added
  • Check for skipped tasks

3. Code Quality Check (from AGENTS.md)

Apply the full review checklist:

  • pnpm verify passes
  • Tests added for all new behavior
  • No unnecessary any types
  • Public APIs have explicit return types
  • Error cases handled
  • No secrets or credentials
  • Conventional Commits format
  • ESM patterns followed (.js extensions, named exports)

4. Security Check

  • User input validated at boundaries
  • SQL queries parameterized
  • File paths sanitized
  • No hardcoded secrets

5. Generate Review Report

## Review Report: KNOW-{NNN}

### Spec Compliance

| Check                   | Status         | Notes    |
| ----------------------- | -------------- | -------- |
| AC-1: ...               | PASS/FAIL/WARN | ...      |
| AC-2: ...               | PASS/FAIL/WARN | ...      |
| Design interfaces match | PASS/FAIL      | ...      |
| Data flow matches       | PASS/FAIL      | ...      |
| All tasks complete      | PASS/FAIL      | X/Y done |

### Code Quality

| Check                  | Status    |
| ---------------------- | --------- |
| pnpm verify            | PASS/FAIL |
| Tests for new behavior | PASS/WARN |
| No unnecessary any     | PASS/WARN |
| Explicit return types  | PASS/WARN |
| Error handling         | PASS/WARN |
| Conventional Commits   | PASS/FAIL |

### Security

| Check                | Status    |
| -------------------- | --------- |
| Input validation     | PASS/N/A  |
| SQL parameterization | PASS/N/A  |
| No secrets           | PASS/FAIL |

### Verdict

APPROVE / REQUEST CHANGES / COMMENT

### Action Items (if any)

1. ...
2. ...

Read the full file on GitHub · 124 lines

Changes

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.

  1. 12d ago First seen · 124 lines · 48 tokens per session scan A 55215af4e577

Subscribe to this mod's changes

sdd-review is a skill published in the GitHub repository 3062-in-zamud/knowledgine (3 stars, last pushed 1mo ago), licensed MIT. It adds 48 tokens to every session and 785 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 2026-08-31.

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