Conciseness

The workspace/path convention (".bensz-api/task-{ts}...") is stated at least four times — in the timestamp section (lines 40-46), the "输出管理" section inside the output template (line 134), the "文件隔离" constraint (line 153), and "公共硬约束" (line 157) — and the ~9-line "公共硬约束" boilerplate covers generic concerns (API keys, SSRF, CHANGELOG, BAC) irrelevant to code recommendation, matching anchor 2's 'several unnecessary explanations or padded sections'. It is above anchor 1 because the core workflow sections are not concept-explanation padding and the scripts/TOML details are appropriately externalized.

Actionability

The body provides copy-paste-ready commands: the workspace setup bash (TS=...; mkdir -p ...), the ranking script invocation with concrete flags (--input, --top-k 50, --prefix A, --output-dir), and the report-skeleton script with a cp to the delivery location, plus a concrete report template. It falls short of anchor 5 because the report-template block around lines 100-117 has a broken/ambiguous code fence — the list and table appear between an unterminated fence and a stray closing ``` — leaving the exact template boundaries unclear.

Workflow Clarity

A clear sequence is present (timestamp/workspace → read-only body ingestion → deterministic coarse ranking → AI semantic selection of 5 pairs → skeleton generation → fill → copy to root), and a "失败与恢复" section covers error recovery, but the "校验" step is vague — "完成后执行 Skill 已有的静态检查、脚本验证或人工复核" names no concrete check or command (the bundled validate_skill.py is never referenced), matching anchor 3's 'validation gaps; checkpoints implicit'. It is above anchor 2 because steps are well defined and ordered, not rough.

Progressive Disclosure

The 678KB recommendation library is correctly externalized to references/nsfc_code_recommend.toml and clearly signaled as "代码推荐覆盖库", and the two workflow scripts (nsfc_code_rank.py, nsfc_code_new_report.py) are referenced by real, one-level-deep paths — the bundle listing confirms they exist. It misses anchor 5 because references/demo/ and scripts/validate_skill.py sit unused in the bundle with no navigation or mention, and the output-file template is inlined into SKILL.md rather than split out.

Specificity

The description names concrete actions — "给出 5 组申请代码1/2（主/次）推荐与理由" (give 5 pairs of primary/secondary application code recommendations with reasons), "输出到 NSFC-CODE-vYYYYMMDDHHmm.md", and "只读，不修改标书" — which on their own would reach anchor 4, but the second-person phrasing "为你给出" (gives you) incurs the mandated 1-point reduction per judging guidelines, landing at anchor 3. It is above anchor 2 because multiple specific actions and an explicit output artifact are named, not just a domain.

Completeness

The "what" is clearly answered (5 code-pair recommendations with reasons, written to a named output file, read-only on the proposal), but there is no "Use when..." clause or equivalent explicit trigger guidance — the use case is only weakly implied by "根据 NSFC 标书正文内容". Per the judging guidelines, a missing explicit 'when' caps completeness at 3, and the clear 'what' keeps it above anchor 2.

Trigger Term Quality

Natural domain terms are present: "NSFC", "标书正文" (proposal body), "申请代码" (application code) — phrases a Chinese grant applicant would actually say when unsure which code to pick. It falls short of anchor 5 because common synonyms and variations such as "基金申请书", "国自然", or "学部/代码选择" are missing, but it clearly exceeds anchor 3's partial coverage.

Distinctiveness Conflict Risk

The niche is extremely specific — NSFC (National Natural Science Foundation of China) application-code selection from a proposal body — with unique triggers ("NSFC", "标书", "申请代码1/2") that no generic document or data skill would match. This matches anchor 5's clear niche with minimal conflict risk; anchor 4's 'minor overlap risk' would understate how distinctive this domain is.