BC habitchat
Personal habit coach that tracks daily habits, streaks, and provides AI-powered coaching. Say things like "track a new habit", "log my habits", "show my streaks", or "coach me".
As a process C 61/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 3
✓ No critical or high findings
Medium and low: 3
-
low Dangerous commands
cmd-cron-mentionscripts/reminder.py:111Mentions editing / listing crontab (string literal in code, not executed)f"To activate, add a cron job: crontab -e and add:\n"
code literal -
low Dangerous commands
cmd-cron-mentionscripts/reminder.py:129Mentions editing / listing crontab (string literal in code, not executed)f"To activate, add a cron job: crontab -e and add:\n"
code literal -
low Dangerous commands
cmd-cron-mentionscripts/reminder.py:200Mentions editing / listing crontab (string literal in code, not executed)f"Remember to also remove the cron job if you added one: crontab -e",
code literal
Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "homepage"
Process rating: all ten parameters 61/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 7 mutating operations with no state check
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 73 steps
- 100Failures and branches. 3 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2434 tokens
- 100Progress reporting. Reports progress
- high The skill tells the model to perform an irreversible action with no human approval
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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -41 reference files, but SKILL.md never points to them: the model will not open them
- +1No license
- +2Single-language instructions
- +5Description quotes 4 example trigger phrases
- +3Description length 177: enough signal without eating the budget
- +4Structure: 23 headings
- +3Step-by-step instructions: 73 items
- +4Has examples (13 code blocks)
- +3All 3 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.
External checks
ClawHub: suspicious
HabitChat is mostly a coherent local habit tracker, but its reminder feature can generate executable shell scripts from unsanitized habit names, creating a command-execution risk if reminders are enabled.
LLM: suspicious (high) · VirusTotal: suspicious · 27 May 2026