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 carta/plugins --skill carta-compensation-scorecardgit clone --depth 1 https://github.com/carta/pluginsWrote 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/carta/plugins/carta-compensation-scorecard)<a href="https://agentmods.dev/skills/carta/plugins/carta-compensation-scorecard"><img src="https://agentmods.dev/badge/skills/carta/plugins/carta-compensation-scorecard.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 133 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 12 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
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 | $0.00215 | $0.12558 |
| Opus 5 | $0.00108 | $0.06279 |
| Sonnet 5 | $0.00043 | $0.02512 |
| Haiku 4.5 | $0.00021 | $0.01256 |
Grade A, and why
carta-compensation-scorecard 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 8d 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 — 600 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CTC Scorecard
Show how a corporation's compensation stacks up against market — at the corp level (band distribution rollup) or at the employee level (per-employee compa-ratio table) — using Carta Total Compensation data.
This skill calls compensation-service's scorecard endpoints (the same endpoints the CTC in-product UI uses) and renders the result in chat. By construction, the output matches what the customer sees in their CTC product surface.
CRITICAL — Casing rule for ALL user-facing CTC values.
Render CTC taxonomy values in Title Case display form, never the UPPER_SNAKE_CASE API enums. Matches the carta-compensation-rolematcher and carta-compensation-benchmarks convention so the plugin's voice is consistent across skills.
Field Use in user-facing text Never Job area Engineering,Sales,Customer Success,Project Management,Human ResourcesENGINEER,SALES,CUSTOMER_SUCCESS,PROJECT_MANAGEMENT,HRFocus DevOps and Site Reliability,Account Executive,FP&Adevops and site reliability,account executive,fp&aLevel Entry,Mid 1,Senior 1,Staff 2,VP 1,C-Level,CEO,UnknownENTRY,MID1,SENIOR1,STAFF2,VP1,C_LEVEL,UNKNOWNTrack IC,Manager,Executive,Unknownic,manager,executive,UNKNOWNBand Low,Mid,Highlow,mid,highThe UPPER_SNAKE_CASE enums are only for machine handoff to MCP commands (the
job_filters,leaderparameters). Switch to Title Case before any value reaches the user.Band enum — the API uses
LOW/MID/HIGH, NOTBELOW_MARKET/AT_MARKET/ABOVE_MARKET. This is the single source of truth:
API value (filter + response) Display Maps to user phrasing LOWLow"below market", "below P50" MIDMid"at market" HIGHHigh"above market", "above P50" Pass
LOW/MID/HIGH(notBELOW_MARKET) as thescorefilter value, and parseLOW/MID/HIGHfrom responsescorefields. Display the actual band value (Low/Mid/High) in tables — do not relabel it to "Below market". When the user asked for a band by market phrasing (e.g. "show me below-market employees"), echo their phrasing in the surrounding prose AND map it to the real enum, e.g. "Here are your below-market (Low) employees:" — but the per-row Band column still showsLow.See
carta-compensation-rolematcher→ "Display → API enum tables" for the full mapping.
Use MCP, not CLI. Every API call in this skill goes through the carta MCP. Do not shell out to the
cartaCLI — that bypasses the formatters, the 403 handler, and the attribution requirement.⚠️ Two different invocation paths in this skill — do not conflate them.
Command Invoke with Why subscription_status,planmcp__carta__call_tool({"name": "compensation__get__…", "arguments": {…}})Registered as flat call_tooltools (the plugin-wide convention, same as the benchmarks skill).employee-scorecard,corporation-scorecardmcp__carta__fetch({"command": "compensation:get:…", "params": {…}})Registered only as MCP commands. They are NOT flat call_tooltools —call_tool({"name": "compensation__get__employee_scorecard"})returns "Unknown tool" and silently wastes calls.The scorecard commands are the trap: an LLM carrying
call_toolmuscle memory from the benchmarks skill will call the wrong tool. In this skill, thecall_tool(...)shorthand is used ONLY forsubscription_statusandplan. Everyemployee-scorecard/corporation-scorecardexample below is written out in full asmcp__carta__fetch(...)— invoke it exactly as written, do not "translate" it back tocall_tool.For the
fetchcommands, note the shapes that trip agents up: the command name is hyphenated/colon (compensation:get:employee-scorecard), the argument key isparams(notarguments), andpage_sizeis snake_case.
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.
- 8d ago First seen · 600 lines · 215 tokens per session scan A 66851a5a01ea
carta-compensation-scorecard is a skill published in the GitHub repository carta/plugins (12 stars, last pushed 3d ago), licensed Apache-2.0. It adds 215 tokens to every session and 12,558 once invoked, about $0.0011 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 2026-08-30.
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