القائمة
Compute summary statistics for a CSV and write a JSON + markdown report. Use when the user asks to analyze, summarize, profile, or compute metrics for a CSV / tabular dataset.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Test or debug a Claude Code skill/plugin under Claude Cowork's runtime — sandboxed agent, default-deny egress, the can_use_tool permission/question protocol — using the cowork-harness CLI. Use when validating or regression-testing a skill, authoring or debugging a scenario YAML (prompt + scripted answers + assert:), choosing a fidelity tier, scripting AskUserQuestion / tool-permission answers, or asserting artifacts, egress, or sub-agent dispatch. Especially when a harness run no-ops an assertion, fails on an unanswered gate, false-greens, a steered answer never reaches the model, or a web_fetch is unexpectedly denied or gated. Also when iterating or hardening a skill across fixes, or grounding a skill's self-critique against its own run evidence — including a document-analysis skill (cap table, deck, financial model, transcript) that needs an uploaded file attached to be critiqued at all. NOT for generic unit testing (pytest/vitest of your own scripts) or non-Cowork CI. Covers the skill / run / chat / record
Live-lane probe — dispatches one sub-agent that must research with the WebSearch tool.
Live-lane probe — reads an attached uploaded file with the Read tool and quotes its marker line.
Internal harness probe for resume-continuity. Use when asked to run the resume-continuity probe, to load the probe skill, or to retrieve the vault passphrase.
fixture skill A — has a candidate source under scripts/
fixture skill B — sibling of skill-a, must be excluded when the target is skill-a directly
| name | csv-metrics |
| description | Compute summary statistics for a CSV and write a JSON + markdown report. Use when the user asks to analyze, summarize, profile, or compute metrics for a CSV / tabular dataset. |
Profiles a CSV and writes two deliverables: a structured metrics.json and a
human-readable summary.md. The work is done by a bundled producer script
(scripts/metrics.py) — you run it, you don't reimplement it.
The user has a CSV (in uploads/ or a connected project folder) and wants
per-column statistics or a metrics report.
Locate the CSV. Default for this example: uploads/sales.csv.
Run the bundled producer, passing the CSV and the output directory. The
script lives under this skill's scripts/ folder, reachable via
${CLAUDE_PLUGIN_ROOT}:
python3 "${CLAUDE_PLUGIN_ROOT}/skills/csv-metrics/scripts/metrics.py" uploads/sales.csv outputs
It writes outputs/metrics.json and outputs/summary.md and prints a
one-line summary.
Read outputs/summary.md, then reply with a single line that includes the
row count and the path outputs/metrics.json.
pip install, no
network. That is deliberate: under Cowork the agent runs with default-deny
egress and no pypi access, so a skill's producer must be self-contained.outputs/ as write-once for the deliverable: don't delete or rewrite
the files after the producer emits them.