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 check-span-and-layersgit 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/check-span-and-layers)<a href="https://agentmods.dev/skills/daddia/claude-for-strategy/check-span-and-layers"><img src="https://agentmods.dev/badge/skills/daddia/claude-for-strategy/check-span-and-layers/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/check-span-and-layers"><img src="https://agentmods.dev/badge/skills/daddia/claude-for-strategy/check-span-and-layers.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 | $0.00058 | $0.01039 |
| Opus 5 | $0.00029 | $0.00519 |
| Sonnet 5 | $0.00012 | $0.00208 |
| Haiku 4.5 | $0.00006 | $0.00104 |
Grade A, and why
check-span-and-layers 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 12d 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 — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Check Span and Layers
When to use
Diagnose span of control and layer count — both over-management (narrow spans, excess layers) and under-management (wide spans where coaching needed).
What this skill does not do
- Does not redesign decision rights — route to
/operating-model:design-decision-rights. - Does not assess strategic structure fit — route to
/operating-model:diagnose-structure-fit. - Does not recommend blanket flattening — changes tied to role-type reasoning.
Preconditions
| Input | If missing |
|---|---|
| Span by function/level | Ask user for org data or HRIS export |
| Layer count top to frontline | Ask; estimate with [review] if partial |
| Practice profile targets | Use industry norms; flag [PROVISIONAL] |
Provisional mode
Partial org data: assess available spans/layers; flag incomplete coverage in output header.
Trust spine
- Confidence bands (
structured-aggregation):- High: Spans assessed by role type; layers justified or flagged; latency estimated.
- Medium: Some functions missing; recommendations qualified.
- Low: No span data — halt.
- Failure modes:
- Strategic advice vs. support: Recommendations are draft for exec/HR review.
- Client confidentiality: Headcount data sensitive — CONFIDENTIAL header.
- Accountability gap: Flags tied to role types, not generic "reduce layers."
- Analytical Rigor: Every function/level in scope assessed.
- Incentive Gaming: N/A for this shape.
- Escalation triggers: Layer count with no complexity justification — flag decision latency cost.
Workflow
- Read practice profile for span/layer data and targets.
- Assess span by function/level against role type (coaching vs. independent work).
- Count layers top to frontline; justify by complexity or flag accumulation.
- Estimate practical cost of excess layers — decision latency, distortion.
- Recommend specific changes with role-type rationale.
- Completeness check before output.
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.
- 12d ago First seen · 108 lines · 58 tokens per session scan A dd491d46916d
check-span-and-layers is a skill published in the GitHub repository daddia/claude-for-strategy (2 stars, last pushed 2mo ago), licensed MIT. It adds 58 tokens to every session and 1,039 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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