AF jd-triage
Career decision system for job seekers. Scores a job description on two independent dimensions — how much you want it (5 weighted axes against your stored criteria) and how likely you are to get it (your skills vs the JD's stated requirements) — then returns one concrete action. Use when (1) the user pastes a job description or recruiter message, (2) the user invokes /jd-triage or asks 'should I apply for this role', (3) the user asks to list, compare, or analyze previously evaluated roles, (4) the user asks what to learn next for a target role, (5) the user asks to set up, update, or reset their career criteria. Market-, language-, and profession-neutral; bootstraps a criteria profile on first run.
As a process F 39/100 · Will not run — References files that are not bundled: assets/presets/*.yaml
How to improve
- The text references files that are not there: add them or drop the references.
- 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: 13. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: assets/presets/*.yaml
Process rating: all ten parameters 39/100
- 0Tools and files. 1 referenced file(s) missing: assets/presets/*.yaml
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 5 mutating operations with no state check
- 70Failures and branches. 11 branches
- 85Steps. 37 steps, 1 vague phrases
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3962 tokens
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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
- -222 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 708: enough signal without eating the budget
- +4Structure: 15 headings
- +3Step-by-step instructions: 37 items
- +4Has examples (2 code blocks)
- +4Reference files are cited in the instructions (5 of 5)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.