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 agentmods add skills/agentculture/learn-cli/challengenpx skills add agentculture/learn-cli --skill challengegit clone --depth 1 https://github.com/agentculture/learn-cliWhat 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 | $0.00183 | $0.03784 |
| Opus 5 | $0.00092 | $0.01892 |
| Sonnet 5 | $0.00037 | $0.00757 |
| Haiku 4.5 | $0.00018 | $0.00378 |
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 yesterday.
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
100% identical to challenge — 0 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 — 291 lines — stays where its author put it; the contents beside it link to each section on GitHub.
challenge — hunt the blind spots before the plan inherits them
The skill is named challenge; it is the blind-spot discovery leg of
the devague method — the seventh origin skill, sitting third in flow
order, between the spec leg and the plan leg:
scope -> think -> challenge -> spec-to-plan -> assign-to-workforce -> deviate -> summarize-delivery
Before this leg existed, a frame could converge on precisely stated claims while the original framing was still incomplete: open questions only captured uncertainty someone had already noticed — nothing actively hunted omitted dimensions, hidden dependencies, or assumptions shared by everyone in the frame, and no record existed of which surfaces were ever examined (issue 73's problem statement). Strictly speaking, an unknown unknown cannot be listed directly — once articulated, it becomes a known unknown. The useful capability is therefore to raise the odds of discovering blind spots and lower the cost of the surprises that remain, not to promise their elimination.
That is the surprise-cost rationale: an articulated blind spot becomes a
known unknown the method can manage; an unexamined one surfaces later as a
mid-run /deviate or a production surprise. Discovery before planning is
cheaper than either — a proposed claim the human rejects costs minutes; the
same gap found mid-fan-out stops a wave, and found in production it costs
whatever the blast radius costs.
This doc is written for two readers. The operator — the main agent — runs
the pass: sweeps the lenses, drives the deterministic CLI move by move, and
proposes findings. The gate-owning human adjudicates: every finding lands
proposed, and confirming, rejecting, or resolving it is the human exercising
the existing spec gate (gate 1) — challenge adds no fourth gate, mirroring
how /deviate amends gate 2 rather than adding one.
When it runs
The timing is a recorded decision — quote it, don't re-derive it:
the challenge pass runs after /think exports: challenge the converged, exported frame before
devague plan new; findings reopen the frame, reconverge, and re-export the same dated spec file — /think stays self-contained (resolves q1)
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.
- yesterday First seen · 291 lines · 183 tokens per session scan A 146e9299f6cc
challenge is a skill published in the GitHub repository agentculture/learn-cli (1 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 183 tokens to every session and 3,784 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to challenge, differing in 0 lines, and is treated as a copy.
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