evaluate-trace

evaluate-trace is a skill for Claude Code from Goodeye-Labs/truesight-mcp-skills. It costs 41 tokens per session (553 once invoked), scanned A, original, MIT.

A workflow for running one or more execution traces through an existing Truesight live evaluation, which is a deployed check that scores or judges inputs.

In plain words
What is it for?
It helps identify the live evaluation, prepare matching inputs, run a single trace or batch, and optionally hand results to review and promotion.
Why use it?
It makes sure the selected evaluation and its required input fields are correct before producing results.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: names the AskUserQuestion tool.

Part of the truesight plugin — 9 skills, 1 MCP server shipped together

Good fit It helps identify the live evaluation, prepare matching inputs, run a single trace or batch, and optionally hand results to review and promotion.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/goodeye-labs/truesight-mcp-skills/evaluate-trace
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 Goodeye-Labs/truesight-mcp-skills --skill evaluate-trace
Clone the repo
git clone --depth 1 https://github.com/Goodeye-Labs/truesight-mcp-skills

Made for: Claude Code.

Or install truesight, the plugin that ships this one along with the rest of its 9 skills, 1 MCP server.

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 evaluate-trace

README.md
[![agentmods](https://agentmods.dev/badge/skills/goodeye-labs/truesight-mcp-skills/evaluate-trace/github.svg)](https://agentmods.dev/skills/goodeye-labs/truesight-mcp-skills/evaluate-trace)
Your own site
<a href="https://agentmods.dev/skills/goodeye-labs/truesight-mcp-skills/evaluate-trace"><img src="https://agentmods.dev/badge/skills/goodeye-labs/truesight-mcp-skills/evaluate-trace/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.

agentmods 80×15 button for evaluate-trace

Your own site · 80×15
<a href="https://agentmods.dev/skills/goodeye-labs/truesight-mcp-skills/evaluate-trace"><img src="https://agentmods.dev/badge/skills/goodeye-labs/truesight-mcp-skills/evaluate-trace.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 553 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.
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 $0.00041 $0.00553
Opus 5 $0.00020 $0.00277
Sonnet 5 $0.00008 $0.00111
Haiku 4.5 $0.00004 $0.00055

Measured 11d ago against content hash ba1992b096f1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

evaluate-trace 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 11d 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.

skills/evaluate-trace/SKILL.md · 61 lines

How it starts

The opening of the file, as written. The whole thing — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Evaluate Trace

Use this skill when the user wants to evaluate traces with an existing live evaluation endpoint.

Interactive Q&A protocol (mandatory)

If context does not make scope clear, ask one question at a time using the structured question tool (loaded per the HARD-GATE above).

Example question structure:

Do you want to evaluate one trace or a batch?
A) One trace now
B) Small batch (up to 25)
C) Full batch loop

Rules:

  • Ask exactly one clarifying question per message.
  • Use the structured question tool for every question. Structure each with a short header, 2-4 options with labels and descriptions, and place the recommended option first. Do not add "(Recommended)" or similar annotations to option labels.
  • Ask a single follow-up if needed, then proceed.

Workflow

  1. Identify target live evaluation:
    • If live evaluation id is unknown, call list_live_evaluations.
    • Select public_id and verify required input_columns.
  2. Prepare inputs:
    • Ensure inputs keys exactly match input_columns.
    • Include media_url for multimodal evaluations when needed.
  3. Execute evaluation:
    • Use the run_eval tool with live_evaluation_id and inputs for each trace.
  4. Return useful outputs:
    • run_id
    • per-judgment scores/outcomes
    • brief interpretation for next action
  5. Optional handoff:
    • If human judgment is needed, route to review-and-promote-traces.

Batch mode guidance

  • Use deterministic trace ordering and log run_id for each input.
  • Apply retries with stable idempotency context in caller logic if needed.
  • Summarize failures by category or threshold, then propose review handoff.

Scopes reference

  • list_live_evaluations requires live-evaluations:read
  • run_eval requires live-evaluations:execute

Read the full file on GitHub · 61 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. 11d ago First seen · 61 lines · 41 tokens per session scan A ba1992b096f1

Subscribe to this mod's changes

evaluate-trace is a skill published in the GitHub repository Goodeye-Labs/truesight-mcp-skills (7 stars, last pushed 5mo ago), licensed MIT. It adds 41 tokens to every session and 553 once invoked, about $0.0002 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.