AC argument-selfloop
Argument self-loop: maintain an argument ledger + premise consistency report for drafted sections. **Trigger**: argument self-loop, argument chain, premise consistency, section self-check, paragraph contract, 论证自循环, 论证链路, 前提一致性, 段落论证动作. **Use when**: you are in C5 (PROSE allowed), `sections/*.md` exist, and you want to prevent “smooth but hollow” writing by enforcing argument moves + premise hygiene before merge. **Skip if**: you are pre-C2 (NO PROSE), or evidence packs are scaffolded/thin (route upstream to `evidence-selfloop` first). **Network**: none. **Guardrail**: do not invent facts; do not add/remove/move citation keys; do not move citations across subsections; the argument ledger is an intermediate artifact and must never be inserted into the paper.
As a process C 61/100 · Has gaps — weak spots: inputs and preconditions, running it twice, progress reporting
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 · 0
✓ No critical or high findings
Files scanned: 19. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 61/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 2 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 60Failures and branches. 2 branches
- 100Steps. 85 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1975 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low The response is described with custom markup (4 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
- +4Description does not say when NOT to use the skill (false activations)
- +1No license
- +2Single-language instructions
- +3Description length 767: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 85 items
- +3Output format is stated explicitly
- +4Has examples (0 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.