zaptrace-benchmark-evaluation

zaptrace-benchmark-evaluation is a skill for Claude Code from oaslananka/zaptrace. It costs 27 tokens per session (505 once invoked), scanned A, original, MIT.

A guide for running and interpreting limited ZapTrace benchmark tests against fixed local test data. Benchmarks are repeatable tests used to compare results under defined conditions.

In plain words
What is it for?
Use it to run synthesis benchmarks, evaluate agent scenarios, review scorecards, compare revisions, and prepare reviewable benchmark evidence.
Why use it?
It helps keep the test data, source version, grading tools, and environment identifiable, so comparisons are easier to check.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the zaptrace plugin — 3 skills, 1 MCP server shipped together

Good fit Use it to run synthesis benchmarks, evaluate agent scenarios, review scorecards, compare revisions, and prepare reviewable benchmark evidence.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/oaslananka/zaptrace/zaptrace-benchmark-evaluation
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 oaslananka/zaptrace --skill zaptrace-benchmark-evaluation
Clone the repo
git clone --depth 1 https://github.com/oaslananka/zaptrace

Made for: Claude Code.

Or install zaptrace, the plugin that ships this one along with the rest of its 3 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 zaptrace-benchmark-evaluation

README.md
[![agentmods](https://agentmods.dev/badge/skills/oaslananka/zaptrace/zaptrace-benchmark-evaluation/github.svg)](https://agentmods.dev/skills/oaslananka/zaptrace/zaptrace-benchmark-evaluation)
Your own site
<a href="https://agentmods.dev/skills/oaslananka/zaptrace/zaptrace-benchmark-evaluation"><img src="https://agentmods.dev/badge/skills/oaslananka/zaptrace/zaptrace-benchmark-evaluation/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 zaptrace-benchmark-evaluation

Your own site · 80×15
<a href="https://agentmods.dev/skills/oaslananka/zaptrace/zaptrace-benchmark-evaluation"><img src="https://agentmods.dev/badge/skills/oaslananka/zaptrace/zaptrace-benchmark-evaluation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 27 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 505 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 $0.00027 $0.00505
Opus 5 $0.00014 $0.00253
Sonnet 5 $0.00005 $0.00101
Haiku 4.5 $0.00003 $0.00051

Measured 9d ago against content hash 1579c2349c0a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

zaptrace-benchmark-evaluation 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 9d 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/zaptrace-benchmark-evaluation/SKILL.md · 78 lines

How it starts

The opening of the file, as written. The whole thing — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ZapTrace Benchmark Evaluation

Use this skill for deterministic ZapTrace benchmark and agent-evaluation workflows against local, committed fixtures.

When to use

Use this skill for:

  • Running the public synthesis benchmark contract
  • Evaluating a bounded agent scenario corpus
  • Reviewing benchmark scorecards and convergence evidence
  • Comparing results across source revisions
  • Preparing machine-readable benchmark evidence for review

Do not use benchmark success to claim general EDA superiority, fabrication readiness, physical correctness, or independent third-party reproduction.

Required inputs

Collect:

  • Benchmark or scenario identifier
  • Committed fixture/corpus path
  • Source revision
  • Grader and tool versions
  • Expected output and policy files
  • Requested comparison baseline, if any

Workflow

  1. Confirm the fixture and policy are committed and integrity-checked.
  2. Use synthesis_benchmark for the public MCP benchmark surface when it matches the requested task.
  3. Use synthesize_board_score only for a bounded preview score; do not commit or export generated state implicitly.
  4. For the twelve-scenario agent corpus, run python scripts/ci_agent_evaluation.py with explicit corpus, policy, JSON output, Markdown output, and artifacts directory arguments.
  5. Preserve raw and normalized evidence, source revision, environment identity, fixture hashes, and grader versions.
  6. Compare only compatible benchmark versions and normalized fields.
  7. Report blocked, skipped, unsupported, and human-review-required outcomes without converting them to passes.

Quality checks

A valid benchmark report must include:

  • Benchmark/corpus identity
  • Source revision
  • Fixture and policy hashes
  • Tool and grader versions
  • Scenario/task results
  • Generated artifact hashes
  • Stop reasons and skipped checks
  • Comparison limitations
  • Independent-reproduction status

Failure modes

Stop and report clearly when:

  • Fixtures or policies are dirty, missing, or unpinned
  • The requested score lacks source or grader identity
  • Results come from incompatible benchmark versions
  • External tools are unavailable and the check cannot be reproduced
  • A repository-controlled rerun is presented as independent third-party evidence

Read the full file on GitHub · 78 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. 9d ago First seen · 78 lines · 27 tokens per session scan A 1579c2349c0a

Subscribe to this mod's changes

zaptrace-benchmark-evaluation is a skill published in the GitHub repository oaslananka/zaptrace (0 stars, last pushed 5d ago), licensed MIT. It adds 27 tokens to every session and 505 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 2026-08-31.

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