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 jeffreytse/grimoire-core --skill design-compensation-structuregit clone --depth 1 https://github.com/jeffreytse/grimoire-coreWrote 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/jeffreytse/grimoire-core/design-compensation-structure)<a href="https://agentmods.dev/skills/jeffreytse/grimoire-core/design-compensation-structure"><img src="https://agentmods.dev/badge/skills/jeffreytse/grimoire-core/design-compensation-structure/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/jeffreytse/grimoire-core/design-compensation-structure"><img src="https://agentmods.dev/badge/skills/jeffreytse/grimoire-core/design-compensation-structure.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 | $0.00027 | $0.01029 |
| Opus 5 | $0.00014 | $0.00515 |
| Sonnet 5 | $0.00005 | $0.00206 |
| Haiku 4.5 | $0.00003 | $0.00103 |
Grade A, and why
design-compensation-structure 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 6d 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 — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design Compensation Structure
Build a defensible, market-aligned compensation structure that attracts, retains, and motivates talent.
Why This Is Best Practice
Adopted by: Mercer, Aon Hewitt, Radford-aligned organizations, and enterprises using structured compensation bands Impact: WorldatWork surveys show organizations with defined salary bands have 18% lower compensation-related turnover and 22% higher offer acceptance rates. Pay equity audits in banded structures identify and close gaps 3x faster than unstructured pay. Why best: Salary bands create internal equity (similar roles paid similarly), external competitiveness (anchored to market data), and career progression clarity (movement through bands signals growth).
Sources: WorldatWork "Total Rewards Model" (2021); Radford Global Technology Survey methodology; SHRM Compensation Management Guide (2023)
Steps
-
Define compensation philosophy — establish the organization's market position: lead (75th percentile), meet (50th percentile), or lag (25th percentile) market. Document the rationale and who it applies to (all roles, technical roles only, executives).
-
Choose a market data source — select 1–3 compensation surveys appropriate to industry and geography (Radford, Mercer, Culpepper, Levels.fyi for tech, Glassdoor/LinkedIn for directional). Match jobs to survey benchmarks, not titles.
-
Define job architecture — create a level framework (e.g., IC1–IC6, M1–M4) with clear scope, impact, and independence criteria for each level. This is the skeleton the bands hang on.
-
Build salary bands — for each level, define minimum, midpoint, and maximum. Standard band width is 50–80% (max ÷ min − 1). Midpoint should equal your target market percentile.
-
Ensure band overlap — adjacent levels should overlap by 25–40%. Overlap allows a top-performing L3 to earn more than an entry L4, preventing forced promotions to get pay increases.
-
Add variable compensation — define bonus targets as % of base salary by level (e.g., IC: 0–15%, M3: 20%, VP: 30%). Document performance linkage, payout timing, and discretionary vs. formulaic structure.
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.
- 6d ago First seen · 63 lines · 27 tokens per session scan A 470d95ad6c5f
design-compensation-structure is a skill published in the GitHub repository jeffreytse/grimoire-core (4 stars, last pushed 21d ago), licensed MIT. It adds 27 tokens to every session and 1,029 once invoked, about $0.0001 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.
Other skills, from other repositories
azure-cost-management-api
In PowerShell, inline JSON for Cost Management API causes "Unsupported Media Type" errors.
stock-analysis-lead
Orchestrate a US-stock investment analysis — classify sector archetype, fetch SEC filings, dispatch a tiered fan-out of six vertical equity-research agents (business model, earnings quality, balance sheet, management, industry, peer comparison) over a validated JSON findings contract, then synthesize a buy/hold/sell…
stock-earnings-quality-review
Review a US-listed company's earnings quality, cash-flow integrity, and operating leverage for an equity-research workup. Covers operating cash flow vs net income drift, free cash flow trajectory, capex character (maintenance vs expansion), equity issuance / shareholder-return yield, revenue-quality signals…
stock-industry-review
Review a US-listed company's industry position and competitive moat for an equity-research workup. Covers Porter Five Forces scan, market-share trend (absolute and relative to industry growth), TAM size and trajectory, unit economics where disclosed (LTV/CAC, unit gross margin), moat classification (network / brand /…
stock-peer-comparison-review
Independently benchmark a US-listed target equity against 2-4 closest peers on a fixed 12-item ratio panel — growth rates, profitability, capital intensity, balance sheet leverage, capital returns, and valuation multiples. Provides cross-validation for moat and market-share claims made by the business and industry…
stock-balance-sheet-review
Review a US-listed company's balance sheet health for an equity-research workup. Covers net-debt/EBITDA leverage, current ratio, cash runway, goodwill concentration and impairment history, DSO trend, inventory days, off-balance-sheet items (operating leases, contingent liabilities), and pension underfunding. Trigger…