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.
git clone --depth 1 https://github.com/TheBeardedBearSAS/claude-craftWrote 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/commands/thebeardedbearsas/claude-craft/audit-freshness)<a href="https://agentmods.dev/commands/thebeardedbearsas/claude-craft/audit-freshness"><img src="https://agentmods.dev/badge/commands/thebeardedbearsas/claude-craft/audit-freshness/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/commands/thebeardedbearsas/claude-craft/audit-freshness"><img src="https://agentmods.dev/badge/commands/thebeardedbearsas/claude-craft/audit-freshness.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 | $0.00023 | $0.02106 |
| Opus 5 | $0.00012 | $0.01053 |
| Sonnet 5 | $0.00005 | $0.00421 |
| Haiku 4.5 | $0.00002 | $0.00211 |
Grade A, and why
audit-freshness 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 9d 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 — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Audit de Fraîcheur claude-craft
Orchestre une équipe de 17 agents parallèles pour vérifier que l'ensemble des skills, commands, agents, references et rules du projet sont alignés avec les dernières versions stables et best practices 2026 des frameworks/outils déclarés. Utilise le MCP Context7 (mcp__context7__resolve-library-id + query-docs) et WebSearch pour les release notes officielles.
Résultat : rapport consolidé docs/audit/freshness-YYYY-MM-DD.md — aucune modification automatique des skills/commands/refs.
Arguments
$ARGUMENTS
--wave=1|2|3|all(défautall) : exécuter uniquement une vague donnée--stack=<nom>: limiter la vague 1 à un stack (symfony, react, flutter, python, angular, laravel, vuejs, reactnative, csharp, php)
MISSION
Étape 1 — Préparer le rapport cible
- Déterminer la date du jour (format YYYY-MM-DD)
- Créer
docs/audit/freshness-<date>.mdavec un en-tête (version claude-craft, date, nombre d'agents lancés, légende écarts : critique/majeur/mineur/aucun) - Relire
.claude/CLAUDE.md(table versions) et.claude/COMPATIBILITY.mdpour la source de vérité des versions déclarées
Étape 2 — Vague 1 : Stacks techniques (10 agents EN PARALLÈLE)
Lancer les 10 agents dans UN SEUL message (10 tool_use Task/Agent). Chaque agent reçoit ce prompt (adapter <STACK>) :
Tu audites la fraîcheur du stack <STACK> dans le dépôt claude-craft.
ÉTAPES :
1. Lire la version déclarée du framework/langage <STACK> dans :
- .claude/CLAUDE.md (table Supported Technologies)
- .claude/references/<stack>/CLAUDE.md et project-context.md
- .claude/agents/<stack>-reviewer.md (frontmatter + body)
- Skills .claude/skills/<stack>-*/SKILL.md
- Commandes .claude/commands/<stack>/*.md
2. Via mcp__context7__resolve-library-id puis mcp__context7__query-docs,
récupérer la version stable actuelle + patterns recommandés 2026.
3. Via WebSearch, vérifier les release notes officielles (site officiel,
GitHub releases) — confirmer version stable, breaking changes, nouvelles
best practices (ex: signals Angular, async Symfony Messenger, etc.).
4. Identifier :
- Écart de version (déclarée vs stable)
- Best practices obsolètes dans les skills/refs/commands
- Patterns nouveaux absents du repo (ex: React Compiler, Flutter Impeller)
5. Retourner EXACTEMENT ce format Markdown (<300 mots) :
## <STACK>
- **Version déclarée** : X.Y (source: <path>:<line>)
- **Version stable actuelle** : X.Y (source: <context7-lib-id> ou <URL>)
- **Écart** : aucun | mineur | majeur | critique
- **Best practices à revoir** :
- <finding> — source: <URL ou context7 ID>
- **Patterns manquants** :
- <pattern> — source: <URL>
- **Fichiers claude-craft impactés** : <path1>, <path2>, ...
- **Sources consultées** : context7=<ids> / web=<urls>
CONTRAINTE : citer systématiquement les sources. Ne rien inventer. Si une
info n'est pas trouvée, écrire "non trouvé" explicitement.
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.
- 9d ago First seen · 177 lines · 23 tokens per session scan A f9907926e4eb
audit-freshness is a command published in the GitHub repository TheBeardedBearSAS/claude-craft (105 stars, last pushed 6d ago), licensed MIT. It adds 23 tokens to every session and 2,106 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 2026-08-30.
Other commands, from other repositories
assemble-team
Assemble a pre-built agent team for parallel work - review, feature, debug, cross-platform, full-stack, or research.
review-code
Trigger a comprehensive code review on recent changes or specified files.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.