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 nataliacorrea03/claude-code-skills --skill fitfogit clone --depth 1 https://github.com/nataliacorrea03/claude-code-skillsWrote 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/nataliacorrea03/claude-code-skills/fitfo)<a href="https://agentmods.dev/skills/nataliacorrea03/claude-code-skills/fitfo"><img src="https://agentmods.dev/badge/skills/nataliacorrea03/claude-code-skills/fitfo/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/nataliacorrea03/claude-code-skills/fitfo"><img src="https://agentmods.dev/badge/skills/nataliacorrea03/claude-code-skills/fitfo.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 | $0.00234 | $0.02506 |
| Opus 5 | $0.00117 | $0.01253 |
| Sonnet 5 | $0.00047 | $0.00501 |
| Haiku 4.5 | $0.00023 | $0.00251 |
Grade A, and why
fitfo 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.
How it starts
The opening of the file, as written. The whole thing — 192 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/fitfo — Figure It The F Out
A decision-forcing skill for situations where the obvious path is blocked, missing, or not good enough. Returns one committed recommendation plus drafts of every artifact the recommendation requires. Never returns a menu.
When to invoke
Explicit triggers
- User types
/fitfo - User says "figure it out", "FITFO it", "I'm stuck", "no good options", "we have to pick something", "I don't know what to do", "this is impossible", "what do I do here"
Auto-detect (model invokes itself) While inside a decision problem, watch what is about to come out of your own mouth. If you catch any of these, stop and invoke FITFO instead:
- "I can't..." / "There's no way to..."
- "The only option is..."
- "We'd need to wait for..."
- "Only you can decide..."
- About to return a list of 3+ options without a recommendation
- "Unfortunately..."
Do not invoke for
- Code-writing tasks ("write me a function that...")
- One-off lookups
- A clear path the user just hasn't started yet
Step 1 — Intake clarity check
Read the problem statement. A problem is sharp if it answers all four:
- What's the actual outcome you want? (the outcome, not the action)
- What specifically is blocked, missing, or not good enough?
- What's already been tried or considered?
- What's the binding constraint? (time, money, people, contractual, brand)
If 3 or 4 are answered, run. If 2 or fewer, run the intake questionnaire below. Do not solve a problem you don't understand.
Step 1a — Intake questionnaire (only if vague)
Use the AskUserQuestion tool. Multi-select where the answer space allows it. Ask in one batch.
- Outcome (free text via Other): "What does 'solved' look like 30 days from now?"
- Blocker (multi-select): missing resource, missing person, no good options on the table, can't decide between options, hard external constraint, internal/political, unknown unknown
- Tried/ruled out (free text via Other): "What's already been tried or considered and rejected?"
- Binding constraint (single-select): time, money, people/headcount, contractual/legal, brand/reputation, energy/attention
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 · 192 lines · 0 tokens per session scan A e1e36aba0490
fitfo is a skill published in the GitHub repository nataliacorrea03/claude-code-skills (4 stars, last pushed 1mo ago), licensed MIT. It adds 234 tokens to every session and 2,506 once invoked, about $0.0012 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.
Other skills, from other repositories
mle-workflow
Production machine-learning engineering workflow for data contracts, reproducible training, model evaluation, deployment, monitoring, and rollback. Use when building, reviewing, or hardening ML systems beyond one-off notebooks.
autonomous-loops
Patterns and architectures for autonomous Claude Code loops — from simple sequential pipelines to RFC-driven multi-agent DAG systems.
react-patterns
React 18/19 patterns including hooks discipline, server/client component boundaries, Suspense + error boundaries, form actions, data fetching, state management decision trees, and accessibility-first composition. Use when writing or reviewing React components.
content-engine
Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.
article-writing
Write articles, guides, blog posts, tutorials, newsletter issues, and other long-form content in a distinctive voice derived from supplied examples or brand guidance. Use when the user wants polished written content longer than a paragraph, especially when voice consistency, structure, and credibility matter.
agent-carnet
Use this skill when the user asks to save, recall, find, or organize notes. Triggers on: 'remember this', 'save this', 'note this', 'what did we discuss about...', 'check the notebook', 'find in carnet'. Also use proactively when discovering findings worth preserving across sessions.