carta-compensation-scorecard

carta-compensation-scorecard is a skill for Claude Code from carta/plugins. It costs 215 tokens per session (12,558 once invoked), scanned A, original, Apache-2.0.

A compensation comparison tool based on Carta Total Compensation data, showing how employee pay compares with the market.

In plain words
What is it for?
Use it to view company-wide pay-band distributions or an employee's comparison-to-market ratio, percentile, and market band.
Why use it?
It replaces separate manual comparisons with summaries for a whole company and scorecards for individual employees.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: model in frontmatter; names the AskUserQuestion tool; positional $N argument.

Part of the carta-cap-table plugin — 22 skills, 5 hooks shipped together

Good fit Use it to view company-wide pay-band distributions or an employee's comparison-to-market ratio, percentile, and market band.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/carta/plugins/carta-compensation-scorecard
Install

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.

Any agent
npx skills add carta/plugins --skill carta-compensation-scorecard
Clone the repo
git clone --depth 1 https://github.com/carta/plugins

Made for: Claude Code.

Or install carta-cap-table, the plugin that ships this one along with the rest of its 22 skills, 5 hooks.

Wrote 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.

agentmods badge for carta-compensation-scorecard

README.md
[![agentmods](https://agentmods.dev/badge/skills/carta/plugins/carta-compensation-scorecard.svg)](https://agentmods.dev/skills/carta/plugins/carta-compensation-scorecard)
Your own site
<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>
Per session 215 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 12,558 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
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.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 8d ago against content hash 66851a5a01ea, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

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.

plugins/carta-cap-table/skills/carta-compensation-scorecard/SKILL.md · 600 lines

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 Resources ENGINEER, SALES, CUSTOMER_SUCCESS, PROJECT_MANAGEMENT, HR
Focus DevOps and Site Reliability, Account Executive, FP&A devops and site reliability, account executive, fp&a
Level Entry, Mid 1, Senior 1, Staff 2, VP 1, C-Level, CEO, Unknown ENTRY, MID1, SENIOR1, STAFF2, VP1, C_LEVEL, UNKNOWN
Track IC, Manager, Executive, Unknown ic, manager, executive, UNKNOWN
Band Low, Mid, High low, mid, high

The UPPER_SNAKE_CASE enums are only for machine handoff to MCP commands (the job_filters, leader parameters). Switch to Title Case before any value reaches the user.

Band enum — the API uses LOW / MID / HIGH, NOT BELOW_MARKET / AT_MARKET / ABOVE_MARKET. This is the single source of truth:

API value (filter + response) Display Maps to user phrasing
LOW Low "below market", "below P50"
MID Mid "at market"
HIGH High "above market", "above P50"

Pass LOW / MID / HIGH (not BELOW_MARKET) as the score filter value, and parse LOW / MID / HIGH from response score fields. 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 shows Low.

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 carta CLI — 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, plan mcp__carta__call_tool({"name": "compensation__get__…", "arguments": {…}}) Registered as flat call_tool tools (the plugin-wide convention, same as the benchmarks skill).
employee-scorecard, corporation-scorecard mcp__carta__fetch({"command": "compensation:get:…", "params": {…}}) Registered only as MCP commands. They are NOT flat call_tool tools — call_tool({"name": "compensation__get__employee_scorecard"}) returns "Unknown tool" and silently wastes calls.

The scorecard commands are the trap: an LLM carrying call_tool muscle memory from the benchmarks skill will call the wrong tool. In this skill, the call_tool(...) shorthand is used ONLY for subscription_status and plan. Every employee-scorecard / corporation-scorecard example below is written out in full as mcp__carta__fetch(...) — invoke it exactly as written, do not "translate" it back to call_tool.

For the fetch commands, note the shapes that trip agents up: the command name is hyphenated/colon (compensation:get:employee-scorecard), the argument key is params (not arguments), and page_size is snake_case.

Read the full file on GitHub · 600 lines

Changes

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.

  1. 8d ago First seen · 600 lines · 215 tokens per session scan A 66851a5a01ea

Subscribe to this mod's changes

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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