SKILLEMALL.ai

BC software-spec-writing

撰寫或更新軟體專案規格文件時必須遵循的流程與結構標準。任何會產生、修改、補充專案文件的任務都要先讀取此 Skill,包含:規格書、需求文件、PRD、架構文件、ADR、業務規則、狀態機、資料模型、API 規格、驗收標準、非功能需求、測試策略;也包含在對話中做出技術決策、確認需求、或發現外部限制之後的文件補寫。當你看到 規格、spec、需求、PRD、文件、架構文件、ADR、驗收標準、AC、涵蓋度、coverage、補文件 等關鍵字,或準備動手寫某個功能的程式碼卻找不到對應規格時,必須讀取並遵循此 Skill。不得自行決定文件結構,也不得憑空生成未經確認的規格內容。

ClawHub Agent Skills author: Jive v1.0.2 MIT-0 7 files body ≈ 2 441 tokens Open the sourceclawhub.ai analyzed 27 h ago

撰寫或更新軟體專案規格文件時必須遵循的流程與結構標準。任何會產生、修改、補充專案文件的任務都要先讀取此 Skill,包含:規格書、需求文件、PRD、架構文件、ADR、業務規則、狀態機、資料模型、API 規格、驗收標準、非功能需求、測試策略;也包含在對話中做出技術決策、確認需求、或發現外部限制之後的文件補寫。當你看到…

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationAI and agentsSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
69
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. 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 · 0

✓ No critical or high findings

Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 53/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 4 mutating operations with no state check
  • 100Tools and files. No external tools needed
  • 100Steps. 37 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2441 tokens
  • 100Progress reporting. Reports progress
  • low 12 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
  • -5TODO / placeholder text left in the skill
  • -248 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 283: enough signal without eating the budget
  • +4Structure: 28 headings
  • +3Step-by-step instructions: 37 items
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (4 of 4)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.

External checks

ClawHub: clean
This is a documentation workflow skill that can strongly shape spec-first development, but its behavior is disclosed, file-scoped, and aligned with its stated purpose.
LLM: benign (high) · VirusTotal: · 17 Aug 2026