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/neurofoo/agent-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/commands/neurofoo/agent-skills/wrap)<a href="https://agentmods.dev/commands/neurofoo/agent-skills/wrap"><img src="https://agentmods.dev/badge/commands/neurofoo/agent-skills/wrap/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/neurofoo/agent-skills/wrap"><img src="https://agentmods.dev/badge/commands/neurofoo/agent-skills/wrap.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 | $0.00000 | $0.00917 |
| Opus 5.5 | $0.00000 | $0.00367 |
| Sonnet 5.5 | $0.00000 | $0.00183 |
| Haiku 4.5 | $0.00000 | $0.00092 |
Grade A, and why
wrap 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 1mo 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 — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
WRAP Decision Framework
Apply the complete WRAP framework to make a better decision by countering the four villains of decision-making.
Instructions
Work through all four phases sequentially. Each phase targets a specific cognitive bias that undermines good decisions.
Output Format
Decision: [What are we deciding?] Context: [Key constraints and stakes]
W: WIDEN Your Options
Counter: Narrow Framing ("Should I do X?" → "What are all my options?")
Current Framing How is the decision currently framed? (Often as "whether or not")
Expanded Options
| # | Option | Why It's Worth Considering |
|---|---|---|
| 1 | [option] | [rationale] |
| 2 | [option] | [rationale] |
| 3 | [option] | [rationale] |
| 4 | [option] | [rationale] |
Option-Finding Techniques Used
- Vanishing options test: "If you couldn't do X, what would you do?"
- Opportunity cost: "What else could you do with this time/money?"
- Find someone who solved it: "Who's had this problem?"
- Multi-track: "What if we tried A and B simultaneously?"
R: REALITY-TEST Your Assumptions
Counter: Confirmation Bias (seeking evidence that confirms what we want)
Key Assumptions
| Assumption | How Would We Know If Wrong? |
|---|---|
| [assumption 1] | [test] |
| [assumption 2] | [test] |
| [assumption 3] | [test] |
Consider the Opposite For each option, what would it take to be convinced it's wrong?
Base Rates What usually happens in situations like this? What's the base rate of success?
Ooch Is there a small experiment we can run to test this before fully committing?
| Option | Small Test | What We'd Learn |
|---|---|---|
| [option] | [test] | [insight] |
A: ATTAIN Distance Before Deciding
Counter: Short-term Emotion (deciding when angry, excited, or desperate)
10/10/10
| Time Horizon | How will you feel about this decision? |
|---|---|
| 10 minutes | [how you feel now] |
| 10 months | [how you'll likely feel] |
| 10 years | [long-term perspective] |
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.
- 1mo ago First seen · 138 lines · 0 tokens per session scan A 7f54f2b93583
wrap is a command published in the GitHub repository neurofoo/agent-skills (122 stars, last pushed 9mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 917 tokens. 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
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.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
speckit.bug.fix
Apply the remediation from a bug assessment and record what was changed.
speckit.bug.test
Validate that a previously fixed bug is resolved and record the verification report.