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 minghinmatthewlam/agent-guards --skill figure-it-outgit clone --depth 1 https://github.com/minghinmatthewlam/agent-guardsWrote 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/minghinmatthewlam/agent-guards/figure-it-out)<a href="https://agentmods.dev/skills/minghinmatthewlam/agent-guards/figure-it-out"><img src="https://agentmods.dev/badge/skills/minghinmatthewlam/agent-guards/figure-it-out/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/minghinmatthewlam/agent-guards/figure-it-out"><img src="https://agentmods.dev/badge/skills/minghinmatthewlam/agent-guards/figure-it-out.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 | $0.00063 | $0.00866 |
| Opus 5.5 | $0.00025 | $0.00346 |
| Sonnet 5.5 | $0.00013 | $0.00173 |
| Haiku 4.5 | $0.00006 | $0.00087 |
Grade A, and why
figure-it-out 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 2d 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
97% identical to figure-it-out — 4 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 — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Figure it out
When the task matches no playbook, design one. The deliverable before any code is the workflow itself: a sequence of phases that scales rigor to the task, runs the scientific method, and leaves a decision trail a human can audit after stepping away.
Start
Open a todolist whose first item is to read the Principles section of the poteto-mode skill. Then add the phases below as todos.
Phase A: Frame
Ground first, then commit. Don't start the run until you can state:
- The definition of done as a falsifiable predicate (the prove-it-works principle skill).
- Scope, quantified: rough units and effort, plus the blockers grounding surfaced.
- The rigor level, biased high. One-way doors and high blast radius get more. Reversible low-stakes steps get less. Rigor is gates and artifacts, not "try harder".
Present the framing and tradeoffs before committing to a long run. Reversible work proceeds (the never-block-on-the-human principle skill), but a multi-hour run earns one checkpoint.
Phase B: Design the workflow
Decompose into atomic, independently-landable units. Sequence riskiest-unknown-first. Scaffold and verification come before features (the foundational-thinking principle skill).
- Build the verification harness before the work, with the baseline captured from the pre-change state, so the check reads as "old value vs new value".
- For one-way-door design decisions, run the architect skill (it runs arena). Skip it for mechanical work whose shape is already concrete. A second arena over a settled design is over-engineering (the laziness-protocol principle skill).
- Decide what fans out. Parallelize only across seams, and give each worker its own worktree or branch (the separate-before-serializing-shared-state principle skill). Don't over-fan.
- Write the designed phase list down. That list is what the human reviews.
Then execute the design. Add its steps to the todolist as concrete items between the Phase C and Phase D entries. Run each under the Phase C loop discipline, and weave the Phase D log through them, a row as each step lands, rather than saving the whole trail for the end.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 53 lines · 63 tokens per session scan A 0ee81b8099af
figure-it-out is a skill published in the GitHub repository minghinmatthewlam/agent-guards (47 stars, last pushed 2d ago), licensed MIT. It adds 63 tokens to every session and 866 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 97% identical to figure-it-out, differing in 4 lines, and is treated as a copy.
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