# Evidence First Research > >- - **Type:** Skill - **Install:** `agentstack add skill-arasz-ai-badger-evidence-first-research` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [Arasz](https://agentstack.voostack.com/s/arasz) - **Installs:** 0 - **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [Arasz](https://github.com/Arasz) - **Source:** https://github.com/Arasz/ai-badger/tree/main/features/common/skills/evidence-first-research - **Website:** https://github.com/Arasz/ai-badger ## Install ```sh agentstack add skill-arasz-ai-badger-evidence-first-research ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # Evidence-first research Answer the question, and make how you know it inseparable from what you found. **Why this exists.** A report where *"the gate takes 75 seconds, measured"* and *"the gate takes about five minutes, roughly"* look identical is a report that will eventually be quoted wrong. That happened here: a cost claim of "3-5 minutes per push, about an hour across fifteen pushes" reached a changelog and a PR body. Measured, it was 75 seconds and nineteen minutes — off by four times, and caught only because someone re-derived it by hand. Nothing in the format made the unmeasured number look unmeasured. So every finding is graded, the grades are a closed set, and the renderer **refuses a record that grades badly** rather than producing a page that looks finished. ## The four grades | Grade | Means | Needs | |---|---|---| | `MEASURED` | You ran it and read the result | The command, the machine, the conditions | | `READ` | You read it in a source that is authoritative for this | `path:line`, a spec section, a doc URL | | `INFERRED` | You reasoned to it from things above | Say what from — reasoning is not a citation | | `UNVERIFIED` | You did not check | Nothing. Saying so *is* the finding | `MEASURED` and `READ` are refused without an `**Evidence:**` line. `UNVERIFIED` is deliberately free: demanding a citation for "nobody looked" pushes writers to leave the gap silent instead, which is the failure this is built to prevent. Full rules in `references/provenance.md` — read it when grading or when a grade is disputed. **The grade is about you, not the claim.** A true fact you did not check is `UNVERIFIED`. A number someone else measured and you copied is `READ`, not `MEASURED` — and if you cannot cite where you read it, it is `INFERRED`. ## Steps 1. **Write the question down first**, as one sentence, before looking anything up. A question that changes shape mid-investigation produces findings that answer neither version. 2. **Investigate.** Prefer running something over reading about it; prefer reading the source over reasoning about it. Every time you drop a level, that is the grade. 3. **Write the record** from `references/report-template.md` into the project's dated-work directory — `/work/YYYY-MM-DD-.md`, per the canonical tree. Grade every finding as you write it, not in a pass at the end: a grading pass is where "I think I measured that" happens. 4. **Render the view:** `python3 .ai-badger/skills/evidence-first-research/scripts/render_report.py /work/YYYY-MM-DD-.md` It writes to a temp directory and prints the path. It **refuses** a target inside the repository — the record is the artefact, and a committed HTML view becomes a second source of truth nobody can date. 5. **Read your own `## Still open` section before reporting.** If it is empty, you either answered everything or you stopped noticing. The second is more common. 6. **Report the grade mix, not just the conclusion.** "Four findings, one measured" is a different answer from "four findings, all measured", and the person acting on it needs to know which. ## Charts Declare one in the record with a fenced block; the renderer turns it into inline SVG. Five kinds, and an unknown kind is refused rather than skipped: | Kind | For | Body | |---|---|---| | `provenance` | The grade mix | Automatic — always drawn, never declared | | `bars` | Comparing measured values | `label: value` per line | | `line` | A quantity across a sequence | `label: v1,v2,v3` | | `matrix` | Options against criteria | Header row, then `label, v, v` | | `range` | A measurement's interval | `label: low..measured..high` | ```chart:range title: push seconds by change shape docs-only: 12..14..19 full: 68..75..91 ``` **Prefer `range` to `bars` for anything timed.** A single bar asserts a precision three runs will not support, and the spread is usually the interesting part. ## Gotchas No environment-specific gotchas known. ## Red flags — STOP - A number in the record with no grade on its finding - `MEASURED` on something you read rather than ran - A benchmark without the machine and the conditions - An empty `## Still open` on a question that took more than an hour - Rendering the HTML into the repository, or committing it - Reporting the conclusion without the grade mix - A `bars` chart of timings, where the spread was never recorded ## Verification checklist - [ ] The question in the record is the question that was asked - [ ] Every `MEASURED` finding names the command and the conditions - [ ] Every `READ` finding cites `path:line` or a spec section - [ ] Every `INFERRED` finding says what it reasons from - [ ] `## Still open` is non-empty, or its emptiness is defended - [ ] The renderer ran clean — it refuses badly graded records, so a clean run is a check - [ ] The HTML is outside the repository and uncommitted ## Files - `references/provenance.md` — what each grade means, what disqualifies one, worked examples. **Read it when grading a finding, or when a grade is disputed.** - `references/report-template.md` — the record shape the renderer parses. **Read it when writing the record (step 3).** - `scripts/render_report.py` — record → self-contained HTML. No network, inline SVG, no scripts. ## Source & license This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [Arasz](https://github.com/Arasz) - **Source:** [Arasz/ai-badger](https://github.com/Arasz/ai-badger) - **License:** MIT - **Homepage:** https://github.com/Arasz/ai-badger Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/skill-arasz-ai-badger-evidence-first-research - Seller: https://agentstack.voostack.com/s/arasz - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.