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 map-incentivesgit 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/map-incentives)<a href="https://agentmods.dev/skills/daddia/claude-for-strategy/map-incentives"><img src="https://agentmods.dev/badge/skills/daddia/claude-for-strategy/map-incentives/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/map-incentives"><img src="https://agentmods.dev/badge/skills/daddia/claude-for-strategy/map-incentives.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 | $0.01185 |
| Opus 5.5 | $0.00024 | $0.00474 |
| Sonnet 5.5 | $0.00012 | $0.00237 |
| Haiku 4.5 | $0.00006 | $0.00119 |
Grade A, and why
map-incentives 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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Map Incentives
When to use
When behavior must be predicted from actual reward/penalty structures — internal stakeholders, competitors, channels, regulators — not stated motivations.
What this skill does not do
- Does not fix misaligned incentives — route structural fixes to
/operating-model:align-rewards-and-incentives. - Does not forecast competitive retaliation — route to
/market-intelligence:forecast-competitive-responseonce maps exist. - Does not accept vague motivations — insists on measurable incentive structures.
Preconditions
| Input | If missing |
|---|---|
| Situation and relevant players named | Ask once to scope |
| Incentive data (comp plan, KPIs, evaluation criteria) | Proceed with [PROVISIONAL] — flag predictions [review]; ask user for specifics |
Provisional mode
Without comp/KPI detail: state predictions as hypotheses from partial data; tag every player Actual incentive structure: incomplete — [review].
Trust spine
- Confidence bands (
hypothesis-driven-analysis):- High: Specific incentive structures cited; behavior predictions falsifiable; divergence analysis complete.
- Medium: Some structures inferred; divergences flagged openly.
- Low: Stated-motivation-only input — refuse to validate as incentive map.
- Failure modes:
- Strategic advice vs. support: Predictions are hypotheses for strategist validation, not behavioral verdicts.
- Client confidentiality: Comp structures may be sensitive — CONFIDENTIAL header.
- Accountability gap: Divergence flags force engagement with misalignment, not silent acceptance.
- Analytical Rigor: MECE player coverage; incentive-before-stated-motivation discipline enforced.
- Incentive Gaming: Names when players may game stated metrics — flag pattern explicitly.
- Escalation triggers: Internal misalignment threatens stated strategy — name as fixable problem, route to operating-model.
Workflow
- Name every player relevant to the situation.
- For each player, state actual incentive structure — measured, paid, evaluated, by whom, what timeframe. Reject "wants success" as substitute.
- Predict behavior from incentive structure alone — before checking stated motivation.
- Compare to stated motivation. Divergence = incentive prediction trusted.
- Flag misaligned incentives as named fixable problems.
- MECE check before output: all relevant players covered.
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 · 114 lines · 61 tokens per session scan A 514c8c09a5a5
map-incentives is a skill published in the GitHub repository daddia/claude-for-strategy (2 stars, last pushed 3mo ago), licensed MIT. It adds 61 tokens to every session and 1,185 once invoked, about $0.0002 per session on Opus 5.5. 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.
Other skills, from other repositories
review
Run the full pre-merge panel: parallel audit and lens reviewers over a diff, consolidated into one severity-ranked verdict.
to-tickets
Slice a spec or a ticket into tracer-bullet tickets with blocking edges, published through the repo's tracker: .specs/tickets/ .md by default.
tdd
Test-driven development, from unit to end-to-end tests. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration or end-to-end tests (Playwright, Cypress). Don't use to backfill tests on existing code (/refactor) or diagnose an unknown bug (/debug).
visual-review
Two visual modes — render a PR diff as an HTML page with each hunk annotated by principle, or check a UI change in a real browser (screenshots, console, network). Use for a visual/HTML diff report, "check the UI", or "screenshot before/after". Don't use for text-only feedback (/code-review), unit tests (/tdd), or full…
to-pr
Gate, push, and open a GitHub pull request on the repo's PR template, then watch CI.
debate
Settle a go/no-go on one risky change against an alternative through an advocate, a skeptic, and a neutral investigator.