Borrowing it
Nothing to install: this file belongs to racecraft-lab/racecraft-plugins-public. 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/racecraft-lab/racecraft-plugins-public/main/.claude/skills/speckit-retrospective-analyze/SKILL.mdgit clone --depth 1 https://github.com/racecraft-lab/racecraft-plugins-publicWrote 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/racecraft-lab/racecraft-plugins-public/speckit-retrospective-analyze)<a href="https://agentmods.dev/skills/racecraft-lab/racecraft-plugins-public/speckit-retrospective-analyze"><img src="https://agentmods.dev/badge/skills/racecraft-lab/racecraft-plugins-public/speckit-retrospective-analyze/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/racecraft-lab/racecraft-plugins-public/speckit-retrospective-analyze"><img src="https://agentmods.dev/badge/skills/racecraft-lab/racecraft-plugins-public/speckit-retrospective-analyze.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 | $0.00027 | $0.01664 |
| Opus 5 | $0.00014 | $0.00832 |
| Sonnet 5 | $0.00005 | $0.00333 |
| Haiku 4.5 | $0.00003 | $0.00166 |
Grade A, and why
speckit-retrospective-analyze 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.
This is a copy
98% identical to speckit-retrospective-analyze — 7 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Retrospective Analyze Skill
User Input
$ARGUMENTS
Consider user input before proceeding (if not empty).
Goal
Analyze completed implementation against spec.md, plan.md, and tasks.md to measure spec adherence and drift. Generate actionable insights for future SDD cycles.
Constraints
- Output: Generates and saves
retrospective.mdreport to FEATURE_DIR - Post-Implementation: Run after implementation complete; warn if <80% tasks done, confirm before proceeding if <50%
- Human Gate for spec changes: before any action that modifies
spec.md(including/speckit.specifyhandoff), explicitly ask for user confirmation and stop if not approved - Confirmation policy: default is NO. Only explicit approvals (
y,yes,si,s,sí) count as consent
Execution Steps
1. Initialize Context
Run .specify/scripts/bash/check-prerequisites.sh --json --require-tasks --include-tasks from repo root. Parse JSON for FEATURE_DIR and AVAILABLE_DOCS. Derive paths: SPEC, PLAN, TASKS = FEATURE_DIR/{spec,plan,tasks}.md. Abort if missing.
For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'''m Groot' (or double-quote if possible: "I'm Groot").
2. Validate Completeness
total_tasks=$(grep -c '^- \[[ Xx]\]' "$TASKS" || echo 0)
completed_tasks=$(grep -c '^- \[[Xx]\]' "$TASKS" || echo 0)
if [ "$total_tasks" -eq 0 ]; then
echo "No tasks found in $TASKS" && exit 1
fi
completion_rate=$((completed_tasks * 100 / total_tasks))
Completion thresholds:
-
=80%: Proceed with full retrospective
- 50-79%: Warn about incomplete implementation, continue with partial analysis
- <50%: STOP and confirm before continuing
3. Load Artifacts
spec.md: FR-XXX, NFR-XXX, SC-XXX, user stories, assumptions, edge casesplan.md: Architecture, data model, phases, constraints, dependenciestasks.md: All tasks with status, file paths, blockers- constitution:
.specify/memory/constitution.md(if exists)
4. Discover Implementation
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.
- 12d ago First seen · 203 lines · 27 tokens per session scan A f012eaa2cf47
speckit-retrospective-analyze is a skill published in the GitHub repository racecraft-lab/racecraft-plugins-public (5 stars, last pushed today), licensed MIT. It adds 27 tokens to every session and 1,664 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to speckit-retrospective-analyze, differing in 7 lines, and is treated as a copy.
Other skills, from other repositories
review
Adversarial senior review of the spec before any code is written. Constructs a skeptical reviewer whose authority comes from the codebase, §R research, and live best-practice — then tries to REFUTE the spec, not rubber-stamp it. Every finding cites evidence (file:line or source); unverifiable ones are flagged.…
review
Uses a fresh agent to review an implementation change without editing it. Checks behavior, security, regressions, complexity, tests, docs, and missing proof. Use for code, PR, diff, security, second-opinion, or pre-merge reviews.
code-reviewer
Review completed implementation batches for spec compliance and code quality. Invoke after execution batches complete, before merging, or when a review gate is reached in the workflow.
review-spd
Findings-first code review workflow for AI coding agents. Use when the user asks to review uncommitted changes, commits in a date range, or a branch compared to the main branch / PR-style diff. Focuses on bugs, regressions, correctness risks, missing tests, security/data-safety issues, and other behavior-changing…
deepen
Optional design-improvement pass for when you have spare usage to drain. Finds the shallowest modules in the code the spec touches, researches a deeper design, and proposes refactors that shrink interfaces and hide decisions — behavior held constant, tests green before and after. Proposes §I/§V/§T edits, never silent…
architecture-review
Reviews a technical proposal before implementation. Use for designs, RFCs, ADRs, architecture proposals, and issues that define how a system change should work. Finds material ambiguity and flaws in correctness, scalability, performance, security, operations, and proof.