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 fzfclee/consulting-skills --skill evidence-mapgit clone --depth 1 https://github.com/fzfclee/consulting-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/fzfclee/consulting-skills/evidence-map)<a href="https://agentmods.dev/skills/fzfclee/consulting-skills/evidence-map"><img src="https://agentmods.dev/badge/skills/fzfclee/consulting-skills/evidence-map/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/fzfclee/consulting-skills/evidence-map"><img src="https://agentmods.dev/badge/skills/fzfclee/consulting-skills/evidence-map.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 | $0.00050 | $0.00814 |
| Opus 5.5 | $0.00020 | $0.00326 |
| Sonnet 5.5 | $0.00010 | $0.00163 |
| Haiku 4.5 | $0.00005 | $0.00081 |
Grade A, and why
evidence-map 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 1mo 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Evidence Map
Use this skill to turn mixed user input into a clear evidence base before making a recommendation.
Method Notes
- Evidence mapping separates what is known, inferred, assumed, missing, and contradicted.
- It is most useful early in a diagnostic, before strong hypotheses or action plans are formed.
- The goal is not to demand perfect proof; it is to prevent weak evidence from carrying strong conclusions.
Required Inputs
Collect or infer these inputs before execution:
- decision or diagnostic question
- raw statements, observations, documents, or claims
- source of each statement when available
- current conclusion or proposed action
- decision deadline or consequence if relevant
If an input is missing, mark it as missing, state the assumption used, and add a validation action.
When Not To Use
Do not use when the facts are already clean and the main need is choosing among options. Use decision-matrix, weighted-scorecard, or effort-impact-matrix instead.
Step-by-Step Execution
| Step | Required input | How to execute | Output |
|---|---|---|---|
| Define the decision question | Decision, objective, current recommendation. | State the question the evidence must support or disprove. | Evidence question. |
| Extract evidence items | Raw notes, claims, observations, artifacts. | Split compound statements into atomic items. Keep one fact or claim per row. | Evidence inventory. |
| Classify item type | Each evidence item, source, timing. | Label each item as fact, direct observation, document, inference, assumption, hearsay, estimate, contradiction, or missing evidence. | Evidence type map. |
| Rate strength and relevance | Source quality, recency, directness, decision linkage. | Rate strength as strong / medium / weak / missing and relevance as high / medium / low. Explain why. | Evidence rating table. |
| Identify evidence gaps | Desired confidence, decision risk, weak or missing rows. | Name the 3-5 gaps most likely to change the conclusion. | Evidence gap list. |
| Convert gaps into tests | Evidence gaps, available access, timeline. | Define the fastest practical way to confirm, disconfirm, or reduce uncertainty. | Validation actions. |
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.
- 1mo ago First seen · 80 lines · 50 tokens per session scan A 172b24ca23ca
evidence-map is a skill published in the GitHub repository fzfclee/consulting-skills (7 stars, last pushed 15d ago), licensed Apache-2.0. It adds 50 tokens to every session and 814 once invoked, about $0.0002 per session on Opus 5.5. 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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