AC jobs-hunter-claw
Unified job hunting automation with Google Sheets — discover jobs, submit applications, and track your pipeline with activity logging. Use when: (1) searching job boards (LinkedIn, Indeed, BuiltIn), (2) tracking application status and interviews, (3) logging recruiter contacts and follow-ups, (4) querying jobs by status/company/role, (5) automating periodic job pipeline checks via cron. Requires Google Sheets + gog CLI. Recommended model: google/gemini-flash-latest.
As a process C 62/100 · Has gaps — weak spots: result and completion, running it twice
How to improve
- 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 · 2
✓ No critical or high findings
Medium and low: 2
-
low Dangerous commands
cmd-shell-rcreferences/google-sheet-setup.md:78Writes to a shell startup file (documentation of a security skill)echo 'export JOB_TRACKER_SPREADSHEET_ID="your-spreadsheet-id"' >> ~/.bashrc
security skill -
low Dangerous commands
cmd-shell-rcSKILL.md:88Writes to a shell startup file (documentation of a security skill)echo 'export JOB_TRACKER_SPREADSHEET_ID="your-google-sheet-id"' >> ~/.bashrc
security skill
Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Unified job hunting automation with Google Sheets — discover jobs,… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
Process rating: all ten parameters 62/100
- 0Result and completion. Does not say what the result is
- 30Running it twice. 14 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash, git) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 24 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2813 tokens
- 100Progress reporting. Reports progress
- low 11 top-level sections: this looks like several domains in one skill
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
- +1No license
- +2Single-language instructions
- +3Description length 470: enough signal without eating the budget
- +4Structure: 43 headings
- +3Step-by-step instructions: 24 items
- +4Has examples (27 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.