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 bestagentkits/agency-skills --skill challengegit clone --depth 1 https://github.com/bestagentkits/agency-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/bestagentkits/agency-skills/challenge)<a href="https://agentmods.dev/skills/bestagentkits/agency-skills/challenge"><img src="https://agentmods.dev/badge/skills/bestagentkits/agency-skills/challenge/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/bestagentkits/agency-skills/challenge"><img src="https://agentmods.dev/badge/skills/bestagentkits/agency-skills/challenge.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 | $0.00077 | $0.01529 |
| Opus 5 | $0.00039 | $0.00764 |
| Sonnet 5 | $0.00015 | $0.00306 |
| Haiku 4.5 | $0.00008 | $0.00153 |
Grade A, and why
challenge 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 — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/em:challenge — Pre-Mortem Plan Analysis
Command: /em:challenge <plan>
Systematically finds weaknesses in any plan before reality does. Not to kill the plan — to make it survive contact with reality.
The Core Idea
Most plans fail for predictable reasons. Not bad luck — bad assumptions. Overestimated demand. Underestimated complexity. Dependencies nobody questioned. Timing that made sense in a spreadsheet but not in the real world.
The pre-mortem technique: imagine it's 12 months from now and this plan failed spectacularly. Now work backwards. Why?
That's not pessimism. It's how you build something that doesn't collapse.
When to Run a Challenge
- Before committing significant resources to a plan
- Before presenting to the board or investors
- When you notice you're only hearing positive feedback about the plan
- When the plan requires multiple external dependencies to align
- When there's pressure to move fast and "figure it out later"
- When you feel excited about the plan (excitement is a signal to scrutinize harder)
The Challenge Framework
Step 1: Extract Core Assumptions
Before you can test a plan, you need to surface everything it assumes to be true.
For each section of the plan, ask:
- What has to be true for this to work?
- What are we assuming about customer behavior?
- What are we assuming about competitor response?
- What are we assuming about our own execution capability?
- What external factors does this depend on?
Common assumption categories:
- Market assumptions — size, growth rate, customer willingness to pay, buying cycle
- Execution assumptions — team capacity, velocity, no major hires needed
- Customer assumptions — they have the problem, they know they have it, they'll pay to solve it
- Competitive assumptions — incumbents won't respond, no new entrant, moat holds
- Financial assumptions — burn rate, revenue timing, CAC, LTV ratios
- Dependency assumptions — partner will deliver, API won't change, regulations won't shift
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.
- 9d ago First seen · 182 lines · 77 tokens per session scan A 9e5cbb367430
challenge is a skill published in the GitHub repository bestagentkits/agency-skills (11 stars, last pushed 2mo ago), licensed MIT. It adds 77 tokens to every session and 1,529 once invoked, about $0.0004 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.
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