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 daddia/claude-for-strategy --skill so-what-sharpenergit clone --depth 1 https://github.com/daddia/claude-for-strategyWrote 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/daddia/claude-for-strategy/so-what-sharpener)<a href="https://agentmods.dev/skills/daddia/claude-for-strategy/so-what-sharpener"><img src="https://agentmods.dev/badge/skills/daddia/claude-for-strategy/so-what-sharpener/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/daddia/claude-for-strategy/so-what-sharpener"><img src="https://agentmods.dev/badge/skills/daddia/claude-for-strategy/so-what-sharpener.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 | $0.00061 | $0.00633 |
| Opus 5 | $0.00030 | $0.00316 |
| Sonnet 5 | $0.00012 | $0.00127 |
| Haiku 4.5 | $0.00006 | $0.00063 |
Grade A, and why
so-what-sharpener 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 10d 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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
So-What Sharpener
When to use
Sharpen observations into insight via observation → implication → insight chain. Smallest Minto unit before full narrative.
What this skill does not do
- Does not skip implication step — catches lazy insights.
- Does not force insight on non-load-bearing facts — "No insight earned" section.
- Does not build full pyramid — use
narrative-builderfor that.
Preconditions
| Input | If missing |
|---|---|
| Observations or data points | Ask user to list |
| Decision context | Ask what decision insights must support |
Provisional mode
Missing decision context: implications literal only; insights tagged [review].
Trust spine
- Analytical Rigor (mandatory): Explicit three-step chain per point; merge redundant insights.
- Per
trust-conventions.mdon tagged figures in observations.
Workflow
For each observation:
- State observation unchanged.
- State implication (literal).
- State insight (so-what for decision).
- Flag observations with no earned insight.
- Group and merge overlapping insights.
Output format
Observation: [...]
→ Implication: [...]
→ Insight: [...]
No insight earned: [...]
Worked example
Input: "Mid-tier ARPU down 12% QoQ." Decision: pricing revert?
Excerpt: Implication: mid-tier spending less; Insight: increase likely priced out intended segment — reconsider pricing [review].
Quality checks before delivering
- Three-step chain per point
- No insight earned section when applicable
- Overlaps merged
Propose profile update
When a stable convention surfaces during this run (thresholds, naming, tone, output format, or recurring corrections), propose a profile update: show the exact diff against ~/.claude/plugins/config/claude-for-strategy/consulting/CLAUDE.md (org-wide facts go to org-profile.md), ask for confirmation, and write only on yes. Only /consulting:practice-setup auto-applies a full profile write.
Outputs
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.
- 10d ago First seen · 84 lines · 61 tokens per session scan A 65a21ce49749
so-what-sharpener is a skill published in the GitHub repository daddia/claude-for-strategy (2 stars, last pushed 2mo ago), licensed MIT. It adds 61 tokens to every session and 633 once invoked, about $0.0003 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.
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