SKILLEMALL.ai

BA Habits

Designs, tracks, and repairs personal habits — streaks, completion rates, routines, and quitting an unwanted one. Use when someone wants to start exercising, reading, meditating, or doing anything every day; when a habit keeps collapsing, a streak just broke, or nothing sticks past week two; when they ask how they are doing with a habit, want a daily check-in, a weekly review, or their completion rate; when quitting smoking, vaping, drinking, sugar, nail biting, or doomscrolling, and when a relapse needs a restart plan; when building a morning or evening routine or stacking a new behavior onto an existing cue; when travel, illness, shift work, ADHD, low mood, or a newborn wrecked the routine; and when accountability partners, stakes, rewards, or environment changes are the lever. Covers frequency rules, streak freezes, habit graduation and retirement. Not for goal setting and milestones (`goals`), whole-life productivity systems (`productivity`), or workout programming (`fitness`).

ClawHub Agent Skills author: Iván v1.0.2 MIT-0 17 files body ≈ 6 129 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process A 82/100 · Runs to the end — weak spots: inputs and preconditions

AnalyzerPersonal productivitytype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
66
Run on models
none yet
Process rating
A
82/100
Runs to the end
Inputs and preconditions w 11
0
Result and completion w 14
60
Execution cost w 6
70
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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: 17. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning body-long SKILL.md body ≈ 6129 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "changelog"

Process rating: all ten parameters 82/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 60Result and completion. Output format stated, no completion criterion
  • 70Execution cost. Instruction body is 6129 tokens
  • 100Tools and files. No external tools needed
  • 100Steps. 42 steps
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 4 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 12 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (5 tags): a typed call is more reliable

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
  • +3Description length 996: 120–800 characters recommended
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 42 items
  • +3Output format is stated explicitly

Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.

External checks

ClawHub: suspicious
This is a coherent local habit-tracking skill, but it needs Review because it can automatically write sensitive shared contacts, health, and finance records without a confirmation gate.
LLM: suspicious (high) · 27 Jul 2026