Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/davistroy/claude-marketplacenpx agentmods add skills/davistroy/claude-marketplace/evaluate-pipeline-outputWrote 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/davistroy/claude-marketplace/evaluate-pipeline-output)<a href="https://agentmods.dev/skills/davistroy/claude-marketplace/evaluate-pipeline-output"><img src="https://agentmods.dev/badge/skills/davistroy/claude-marketplace/evaluate-pipeline-output/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/davistroy/claude-marketplace/evaluate-pipeline-output"><img src="https://agentmods.dev/badge/skills/davistroy/claude-marketplace/evaluate-pipeline-output.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 | $0.00071 | $0.06939 |
| Opus 5 | $0.00036 | $0.03469 |
| Sonnet 5 | $0.00014 | $0.01388 |
| Haiku 4.5 | $0.00007 | $0.00694 |
Grade A, and why
evaluate-pipeline-output 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 — 497 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pipeline Output Evaluator
Perform a comprehensive semantic quality evaluation of a contact-center-lab pipeline run. This skill reads pipeline source code to discover schemas and configuration, then reads every key output file, compares content against expectations derived from both the code and the input, and produces a structured report with severity-rated findings.
This skill is read-only. It never modifies files, commits, or pushes.
[!WARNING] Scope: Specialized for the contact-center-lab pipeline. Not generalizable without substantial rewrite. See
LAB_NOTEBOOK.mdin that project for pipeline schema.
Input
Arguments: $ARGUMENTS
Required:
<output-dir>— path to the pipeline output directory (e.g.,./output/single-2026-03-05-1803)
Optional:
--input <path>— path to input fixture/data directory, used to read raw source articles for comparison--baseline <previous-output-dir>— path to a prior run's output directory for regression comparison--mode test|validation|production— adjusts severity thresholds (default:validation)
Usage:
/evaluate-pipeline-output ./output/single-2026-03-05-1803
/evaluate-pipeline-output ./output/full-run-2026-03-06 --baseline ./output/full-run-2026-03-04
/evaluate-pipeline-output ./output/test-5 --input ./pipeline/tests/fixtures/five --mode test
If the output directory is not provided, ask the user which run to evaluate.
Core Principle: Derive, Don't Hardcode
This skill must never be a source of truth for anything the pipeline already defines. Field names, thresholds, file names, expected ranges, and schemas all change as the pipeline evolves. The skill discovers these at runtime from two sources:
- Pipeline source code (schemas, configuration, stage contracts)
- Output data (actual file contents, record structures,
_metablocks)
Every evaluation phase starts with discovery. Python snippets in this skill express intent ("print all triples in subject → predicate → object form"), not field names ("access t['subject_label']"). When this skill says "the field for X," it means "find the field that represents X by inspecting the data."
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 497 lines · 71 tokens per session scan A bde76fc1c66a
evaluate-pipeline-output is a skill published in the GitHub repository davistroy/claude-marketplace (5 stars, last pushed 5d ago), licensed MIT. It adds 71 tokens to every session and 6,939 once invoked, about $0.0004 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 2026-09-04.
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