SKILLEMALL.ai

BF intent-engineering

A meta-framework for designing, building, and orchestrating an ecosystem of strategically-aligned agent skills. This skill governs how the agent itself operates, ensuring that all created skills work together as a cohesive, transparent, and governable system aligned with your organization's goals and values.

ClawHub Agent Skills author: Daniel Foo Jun Wei v1.0.0 MIT-0 18 files body ≈ 1 403 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process F 28/100 · Will not run — References files that are not bundled: references/data_contracts/

GeneratorAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
100
Quality 40%
63
Run on models
none yet
Process rating
F
28/100
Will not run
References files that are not bundled: references/data_contracts/
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. 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: 18. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: references/data_contracts/

Process rating: all ten parameters 28/100

Will not run. References files that are not bundled: references/data_contracts/
  • 0Tools and files. 1 referenced file(s) missing: references/data_contracts/
  • 0Result and completion. Does not say what the result is
  • 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
  • 30Running it twice. 3 mutating operations with no state check
  • 40Consistency. Frontmatter name (intent-engineering) differs from the folder (intent-engineer)
  • 100Steps. 22 steps
  • 100Execution cost. Instruction body is 1403 tokens

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)
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • -32 of 3 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 309: enough signal without eating the budget
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 22 items
  • +4Reference files are cited in the instructions (3 of 8)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.

External checks

ClawHub: suspicious
This skill is not proven malicious, but it broadly governs agent behavior and includes unsafe workflow code that can run arbitrary Python from workflow conditions.
LLM: suspicious (high) · VirusTotal: · 29 May 2026