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 pnp/sharepoint-skills --skill scorecard-matrixgit clone --depth 1 https://github.com/pnp/sharepoint-skillsWrote 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/pnp/sharepoint-skills/scorecard-matrix)<a href="https://agentmods.dev/skills/pnp/sharepoint-skills/scorecard-matrix"><img src="https://agentmods.dev/badge/skills/pnp/sharepoint-skills/scorecard-matrix/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/pnp/sharepoint-skills/scorecard-matrix"><img src="https://agentmods.dev/badge/skills/pnp/sharepoint-skills/scorecard-matrix.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 | $0.00131 | $0.01869 |
| Opus 5 | $0.00066 | $0.00934 |
| Sonnet 5 | $0.00026 | $0.00374 |
| Haiku 4.5 | $0.00013 | $0.00187 |
Grade A, and why
scorecard-matrix 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 10d 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 — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scorecard Matrix
Generates a complete, self-contained HTML scorecard by (1) interviewing the user or parsing their data, (2) constructing and validating a JSON document, then (3) rendering that JSON into HTML using assets/scorecard-matrix-template.html. The JSON is the authoritative source of truth; the HTML is fully determined by it.
Step 1: Determine the Data Source
Check what the user has already provided before asking anything:
- SharePoint list or table: Parse all rows. Identify entities (the things being compared) and scoring columns (the dimensions).
- CSV or table pasted in chat: Extract entities, dimension names, and scores directly. Do not ask for data you already have.
- Verbal description only: Proceed to Step 2.
Step 2: Interview the User
If the data or intent is not fully clear, ask these questions in a single message — not one at a time:
- What are you comparing? List the entities: vendors, tools, candidates, sites, products, options. (2–10 items.)
- What are the criteria? List the dimensions you are scoring against: features, cost, fit, support, risk, readiness, etc. (2–10 items.)
- Weights: How important is each dimension relative to the others? Can be given as percentages (must sum to 100%), ratios (e.g. 3:2:1), or plain priority ranking. The skill normalizes to decimals summing to 1.0.
- Scores: For each entity × dimension cell: what is the score? Use whichever scale feels natural — the skill will ask you to confirm the scale (1–5 or 1–10). If scores come from data, extract them. If from judgment, prompt the user to rate each combination.
- Cell notes: For any cell, is there a short phrase (under 6 words) that explains the score? Optional but valuable.
- Context sentence: One or two sentences describing the decision being made, the audience, and the date or period.
- Palette: Warm paper (cream/terra-cotta), deep ink (dark/gold), clean white (white/green), or slate (gray/blue)? Default to warm paper.
What ships with it
3 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.
- 10d ago First seen · 160 lines · 131 tokens per session scan A 7173967513e0
scorecard-matrix is a skill published in the GitHub repository pnp/sharepoint-skills (112 stars, last pushed yesterday), licensed MIT. It adds 131 tokens to every session and 1,869 once invoked, about $0.0007 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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