Is hypothesis-tracking safe to install?

SaferSkills independently audited hypothesis-tracking (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.

CategoryWeightCategory scoreContribution

Securityprompt, exec, net, exfil, eval

35%

100

35.0 pts

Supply chainhash, typosquat, maintainer, lockfile

20%

100

20.0 pts

Maintenancestaleness, pinning, CI

15%

100

15.0 pts

TransparencySKILL.md, perms, README

15%

100

15.0 pts

Communityinstalls, verify, response

15%

100

15.0 pts

Findings & checks · 0 flagged

Securityscore 100 · 0 findings

✓—All security checks passedNo findings in this category for the latest scan.pass

Supply chainscore 100 · 0 findings

✓—All supply chain checks passedNo findings in this category for the latest scan.pass

Maintenancescore 100 · 0 findings

✓—All maintenance checks passedNo findings in this category for the latest scan.pass

Transparencyscore 100 · 0 findings

✓—All transparency checks passedNo findings in this category for the latest scan.pass

Communityscore 100 · 0 findings

✓—All community checks passedNo findings in this category for the latest scan.pass

The primary manifest — the file an agent reads to learn what this artifact does.

skills/hypothesis-tracking/SKILL.md · 1 file

skills/hypothesis-tracking/SKILL.md1.3 KB · Markdown

name: hypothesis-tracking

version: "1.1.0"

description: "Retrieve and update company hypotheses in Primr. Use when the user asks what is already known, wants to validate a claim, or wants to persist a research finding."

mcp_server: "primr"

tools:

- get_hypotheses

- save_hypothesis

resources:

- primr://context

Hypothesis Tracking

Purpose

Use this skill to manage durable research memory for a company. Hypotheses are a working memory layer, not final truth.

Workflow

Retrieve hypotheses before starting duplicate research.
Present confidence clearly: untested, validated, invalidated, or confirmed.
Update confidence only when new evidence exists.
Keep evidence strings short, factual, and source-oriented.

Operating Rules

Distinguish known facts from open hypotheses.
Preserve the evidence trail when confidence changes.
Prefer updating an existing hypothesis over creating duplicates.
Expired or weak hypotheses should be re-validated before being presented as current.

Example

get_hypotheses(company="ExampleCo", topic="technology")
save_hypothesis(company="ExampleCo", hypothesis_id="h_001", confidence="validated", evidence="CTO interview confirms AWS usage")

hypothesis-tracking— agent skill

Is hypothesis-tracking safe to install?

Hypothesis Tracking

Purpose

Workflow

Operating Rules

Example

Audit the pieces. Scan the whole. Decide.