SKILLEMALL.ai

AF industry-learning-sprint

Activate when: user is entering an unfamiliar industry and needs a working mental model fast; user says 'I need to understand this sector before a meeting next week'; user is evaluating an acquisition or investment in a domain they don't know; user is preparing for a high-stakes expert conversation with limited time; user needs to produce an investment thesis or market entry recommendation under time pressure. Do NOT activate when: user already has deep domain expertise in the target industry; user needs regulatory or legal precision — engage domain-specific counsel instead. More: deciqai.com/c/industry-learning-sprint

ClawHub Agent Skills author: deciqAI v1.0.4 MIT-0 4 files body ≈ 2 232 tokens Open the sourceclawhub.ai analyzed 2 d ago

Activate when: user is entering an unfamiliar industry and needs a working mental model fast; user says 'I need to understand this sector before a meeting…

As a process F 44/100 · Will not run — References files that are not bundled: ../../probabilistic-thinking/SKILL.md, ../../first-principles/SKILL.md, ../../confirmation-bias/SKILL.md

ProcedureOperations and projectstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
75
Run on models
none yet
Process rating
F
44/100
Will not run
References files that are not bundled: ../../probabilistic-thinking/SKILL.md, ../../first-principles/SKILL.md, ../../confirmation-bias/SKILL.md
Tools and files w 18
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: ../../probabilistic-thinking/SKILL.md
  • warning missing-ref reference to a missing file: ../../first-principles/SKILL.md
  • warning missing-ref reference to a missing file: ../../confirmation-bias/SKILL.md

Process rating: all ten parameters 44/100

Will not run. References files that are not bundled: ../../probabilistic-thinking/SKILL.md, ../../first-principles/SKILL.md, ../../confirmation-bias/SKILL.md
  • 0Tools and files. 3 referenced file(s) missing: ../../probabilistic-thinking/SKILL.md, ../../first-principles/SKILL.md, ../../confirmation-bias/SKILL.md
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 60Result and completion. Output format stated, no completion criterion
  • 100Steps. 27 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2232 tokens
  • 100Running it twice. Mutating operations check current state

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +3Description length 626: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 27 items
  • +3Output format is stated explicitly
  • +4Reference files are cited in the instructions (1 of 1)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

External checks

ClawHub: clean
This is a markdown-only learning framework for researching an unfamiliar industry, with no executable code or hidden privileged behavior found.
LLM: benign (high) · VirusTotal: · 16 Jul 2026