reasoning — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited reasoning (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.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
When this skill triggers, call the reasoning tool from the ejentum MCP server. Pass a 1-2 sentence framing of WHAT you are reasoning about as the query argument. Be specific about the task, not what tool you want.
Good query: diagnose why a microservice returns 503s under load Bad query: help me think
The tool returns a structured scaffold containing:
[NEGATIVE GATE]: failure pattern to avoid[PROCEDURE]: steps to follow[REASONING TOPOLOGY]: decision flow with gates and traps[TARGET PATTERN]: correct shape your reasoning should take[FALSIFICATION TEST]: self-check criterionAmplify: signals to engageSuppress: failure modes to blockAbsorb the scaffold internally and shape your response with it. The bracketed fields are instructions, not content to display. Do NOT echo the bracket labels, do NOT name the topology, do NOT meta-comment on calling the tool. The user-facing reply is naturally phrased and shaped by the injection.
If the API is unreachable or returns an error, proceed with native reasoning. The scaffold enhances; it is not a hard dependency.
Latency cost: ~1 second. Benefit: reasoning quality the model cannot reliably reproduce on its own for non-trivial tasks.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.