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 fabioc-aloha/Alex_Skill_Mall --skill repository-readiness-evalgit clone --depth 1 https://github.com/fabioc-aloha/Alex_Skill_MallWrote 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/fabioc-aloha/alex_skill_mall/repository-readiness-eval)<a href="https://agentmods.dev/skills/fabioc-aloha/alex_skill_mall/repository-readiness-eval"><img src="https://agentmods.dev/badge/skills/fabioc-aloha/alex_skill_mall/repository-readiness-eval/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/fabioc-aloha/alex_skill_mall/repository-readiness-eval"><img src="https://agentmods.dev/badge/skills/fabioc-aloha/alex_skill_mall/repository-readiness-eval.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 | $0.00059 | $0.02347 |
| Opus 5 | $0.00030 | $0.01174 |
| Sonnet 5 | $0.00012 | $0.00469 |
| Haiku 4.5 | $0.00006 | $0.00235 |
Grade A, and why
repository-readiness-eval 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 — 270 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repository Readiness Evaluation
Systematic 4-axis assessment of whether a repository is ready for productive AI-assisted development — from code comprehension through successful test execution.
When to Use
- Onboarding to an unfamiliar repository
- Assessing if a codebase is AI-agent-ready
- Validating CI/CD pipeline health
- Pre-engagement quality check before committing to a project
- Measuring improvement after fixing build/test issues
The 4 Axes
| Axis | Question | Score Range |
|---|---|---|
| A: Code Understanding | Can you comprehend the project structure, tech stack, and architecture? | 0–5 |
| B: Dependency Restore | Can you install/restore all dependencies successfully? | 0–5 |
| C: Build Success | Does the project compile/build without errors? | 0–5 |
| D: Test Execution | Do tests run and pass? | 0–5 |
Total: 0–20 points → Tier classification (below)
Phase 1: Code Understanding (Axis A)
Investigation Steps
- Read README — does it explain setup, architecture, and conventions?
- Identify tech stack — languages, frameworks, build system, package manager
- Map project structure — entry points, module boundaries, config files
- Find build/run commands — documented or discoverable from manifests
- Identify test framework — what runs tests, where are they located
Scoring Rubric
| Score | Criteria |
|---|---|
| 5 | Clear docs, standard structure, obvious entry points, well-organized |
| 4 | Minor gaps but navigable — missing some docs, non-standard naming |
| 3 | Understandable with effort — sparse docs, complex structure |
| 2 | Confusing — unclear entry points, mixed concerns, minimal docs |
| 1 | Barely comprehensible — no docs, non-standard everything |
| 0 | Cannot determine project purpose or structure |
Phase 2: Dependency Restore (Axis B)
Investigation Steps
- Identify package manager — npm, pip, dotnet, cargo, maven, etc.
- Run restore command —
npm install,pip install -r requirements.txt,dotnet restore, etc. - Check for lock files —
package-lock.json,poetry.lock,Cargo.lock - Identify private registries —
.npmrc,nuget.config,pip.conf - Record failures — classify per taxonomy below
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 · 270 lines · 59 tokens per session scan A 92e4abbb191a
repository-readiness-eval is a skill published in the GitHub repository fabioc-aloha/Alex_Skill_Mall (4 stars, last pushed today), licensed MIT. It adds 59 tokens to every session and 2,347 once invoked, about $0.0003 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 2026-09-03.
Other skills, from other repositories
programming-advisor
Evaluate existing solutions (libraries, SaaS, open source) AND internal prior-art before custom development to avoid reinventing the wheel. Use when considering building new features, asking "should I build or use existing", "do we already have this", "is there existing code for X in this repo", "is there a library…
ai-agents-portability-campaign
Execute cross-harness hook changes for Claude Code and GitHub Copilot CLI using the settled official contract, versioned probes, generators, and runtime tests. Use for run the portability campaign, port hooks to a new harness, copilot hook timeout regression, or new copilot cli release, recheck the contract. Do NOT…
memory-enhancement
Manage memory citations, verify code references, and track confidence scores. Use when adding citations to memories, checking memory health, or verifying code references are still valid. Use when you say "add a citation", "verify this memory's code refs", "check memory health". Do NOT use for searching or creating…
pre-mortem
Guide prospective hindsight analysis to identify project risks before failure occurs. Teams imagine the project has failed spectacularly, then work backward to identify causes. Increases risk identification by 30% compared to traditional planning. Use when you say "run a pre-mortem on", "what could cause this to…
decision-critic
Structured decision critic that systematically stress-tests reasoning before commitment surfacing hidden assumptions verifying claims and generating adversarial perspectives to improve decision quality. Do NOT use to surface failure risks pre-launch (use pre-mortem) or to probe why a constraint exists (use…
panning-for-gold
Triage raw unstructured input (transcripts, brain dumps) into evaluated thread inventories and a synthesized gold-found file. Four phases: front-gate, extract, evaluate, synthesize. Use when you say "pan for gold", "triage transcript", "synthesize gold-found", or hand it a voice transcript or brain dump. Do NOT use…