Agent Skills Platform turns documented work and supporting evidence into tested, installable skills for coding agents. Teams use it to review, publish, maintain, and safely reuse agent workflows, with the catalogue entries serving as skills and plugins built for that ecosystem.
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.
npx skills add FrancyJGLisboa/agent-skill-creator --skill weekly-crm-reportgit clone --depth 1 https://github.com/FrancyJGLisboa/agent-skill-creatorWrote 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/francyjglisboa/agent-skill-creator/weekly-crm-report)<a href="https://agentmods.dev/skills/francyjglisboa/agent-skill-creator/weekly-crm-report"><img src="https://agentmods.dev/badge/skills/francyjglisboa/agent-skill-creator/weekly-crm-report/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/francyjglisboa/agent-skill-creator/weekly-crm-report"><img src="https://agentmods.dev/badge/skills/francyjglisboa/agent-skill-creator/weekly-crm-report.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00049 | $0.00630 |
| Opus 5 | $0.00024 | $0.00315 |
| Sonnet 5 | $0.00010 | $0.00126 |
| Haiku 4.5 | $0.00005 | $0.00063 |
Grade A, and why
weekly-crm-report 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.
How it starts
The opening of the file, as written. The whole thing — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Weekly CRM Report
Turn a raw weekly CRM export (CSV) into a clean regional sales summary: drop duplicate rows, total revenue per region, and emit a structured JSON summary an agent can narrate or hand to a PDF/dashboard step.
This is a bundled example skill — small but real, and used to demonstrate the creator's validation, pipeline, and eval-rollout machinery end to end.
Activation
Activates on requests like "clean this CRM export", "weekly sales report", "regional totals from this CSV". Do not activate on general spreadsheet or analytics questions that don't involve a CRM export.
Input
A CSV with at least region and amount columns (extra columns are ignored).
Duplicate rows (identical across all columns) are removed before totalling.
Run
One command produces the summary:
python3 scripts/run_pipeline.py --input <export.csv> --output summary.json
Output JSON shape:
{
"rows_in": 120,
"rows_after_dedup": 118,
"regions": {"West": 40210.5, "East": 38110.0},
"grand_total": 78320.5
}
Gotchas
rows_after_dedupdoes not reconcile withgrand_total. Rows with a blank or missingregionare skipped when totalling but still counted inrows_after_dedup, so a CSV with unassigned rows reports more rows than it actually summed. Do not present the two numbers as if one explains the other — if they must reconcile, filter blank regions before running.- An unparseable
amountsilently becomes0.0, it does not raise. A column ofN/Aor—produces a region total of0.0that looks like a real zero. Check the input for non-numeric amounts before trusting a suspiciously low total. - Dedup compares every column, not just
regionandamount. Two rows with identical sales data but a differing timestamp or record-ID column are both kept. The "extra columns are ignored" note above applies to totalling, not to dedup.
Anti-goals
- Not a general BI tool; it totals one numeric column per region.
- Does not fetch from a live CRM API; it operates on an exported CSV.
What ships with it
18 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.
- discovery.json 1.9 KB
- evals/golden/case-1/expected.json 126 B
- evals/golden/case-1/input.csv 62 B
- evals/golden/case-2/expected.json 129 B
- evals/golden/case-2/input.csv 46 B
- evals/golden/case-3/expected.json 106 B
- evals/golden/case-3/input.csv 39 B
- evals/weekly-crm-report.eval.md 1.8 KB
- README.md 1.6 KB
- scripts/dependency_health.py 3.9 KB runs code
- scripts/evolve.py 8.2 KB runs code
- scripts/review_staleness.py 6.2 KB runs code
- scripts/run_evals.py 47 KB runs code
- scripts/run_pipeline.py 2.3 KB runs code
- scripts/schema_drift.py 7.3 KB runs code
- scripts/skill_document.py 9.8 KB runs code
- scripts/staleness_check.py 7.5 KB runs code
- scripts/success_ledger.py 16 KB runs code
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.
- 11d ago First seen · 70 lines · 49 tokens per session scan A 8d2b9228bb8d
weekly-crm-report is a skill published in the GitHub repository FrancyJGLisboa/agent-skill-creator (2,378 stars, last pushed 7d ago), licensed MIT. It adds 49 tokens to every session and 630 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 2026-08-30.
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