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BF diet-log

饮食记录与营养分析助手。当用户提到"饮食记录"、"记下我吃了"、"营养分析"、"统计饮食"、"最近X天吃了什么"等关键词时触发。功能包括：(1) 解析用户输入的饮食内容并查询营养数据；(2) 计算并记录全部营养素（热量、宏量营养素、脂肪酸、矿物质、维生素）；(3) 将饮食记录存入 meal_log.json；(4) 支持阶段性营养统计（按日/周/月）。食物营养数据文件 food_data.json 需单独下载（见 SKILL.md 同目录下的说明或 GitHub 仓库）。食物匹配采用三级策略：精确匹配 → 同类参考 → 提问确认。

ClawHub Agent Skills author: sj13818161942 v1.0.0 MIT-0 6 files body ≈ 1 192 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 37/100 · Will not run — References files that are not bundled: references/food_data.json, references/meal_log.json

ReferenceGitHubInfrastructureAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
60
Run on models
none yet
Process rating
F
37/100
Will not run
References files that are not bundled: references/food_data.json, references/meal_log.json
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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.
  2. The text references files that are not there: add them or drop the references.
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: 6. 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")
  • warning missing-ref reference to a missing file: references/food_data.json
  • warning missing-ref reference to a missing file: references/meal_log.json

Process rating: all ten parameters 37/100

Will not run. References files that are not bundled: references/food_data.json, references/meal_log.json
  • 0Tools and files. 2 referenced file(s) missing: references/food_data.json, references/meal_log.json
  • 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
  • 100Steps. 25 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1192 tokens
  • 100Running it twice. No mutating operations
  • 100Progress reporting. Reports progress

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
  • -32 of 2 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 268: enough signal without eating the budget
  • +4Structure: 21 headings
  • +3Step-by-step instructions: 25 items
  • +4Has examples (4 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.

External checks

ClawHub: clean
The skill appears to be a local meal or nutrition helper whose local food database and meal-log persistence are purpose-aligned and disclosed, though users should treat saved dietary logs as sensitive personal data.
LLM: benign (medium) · VirusTotal: · 29 May 2026