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DD likes-training-planner

Complete training plan solution for My Likes platform. Fetches historical data, analyzes training patterns, generates personalized plans, converts to Likes format, and pushes to calendar. All-in-one skill for running, cycling, swimming, and strength training.

Not recommendedcritical or high security findings · low grade D
ClawHub Agent Skills author: yinshu v1.0.0 MIT-0 46 files · 2 scripts body ≈ 1 956 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process D 39/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerPersonal productivityInfrastructuretype 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
D
45/100
safety, quality, tests
Safety 60%
28
Quality 40%
71
Run on models
none yet
Process rating
D
39/100
Unfinished process
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

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Dangerous commands
If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. 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 · 4

  • high Dangerous commands cmd-pipe-to-shell README.en.md:35
    Downloads and executes remote code from an unrecognised host (pipe to shell)
    curl -fsSL https://gitee.com/chenyinshu/likes-training-planner/raw/main/install.sh | bash
  • high Dangerous commands cmd-pipe-to-shell README.md:37
    Downloads and executes remote code from an unrecognised host (pipe to shell)
    curl -fsSL https://gitee.com/chenyinshu/likes-training-planner/raw/main/install.sh | bash
  • high Dangerous commands cmd-pipe-to-shell README.zh.md:35
    Downloads and executes remote code from an unrecognised host (pipe to shell)
    curl -fsSL https://gitee.com/chenyinshu/likes-training-planner/raw/main/install.sh | bash
  • high Dangerous commands cmd-pipe-to-shell SKILL.md:308
    Downloads and executes remote code from an unrecognised host (pipe to shell)
    curl -fsSL https://gitee.com/chenyinshu/likes-training-planner/raw/main/install.sh | bash

Files scanned: 25. 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 39/100

  • 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
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 14 mutating operations with no state check
  • 40Consistency. Frontmatter name (likes-training-planner) differs from the folder (grouptraining)
  • 60Tools and files. Uses tools (bash, web, node) that frontmatter does not declare
  • 100Steps. 8 steps
  • 100Execution cost. Instruction body is 1956 tokens

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
  • -2localhost URLs: will not work for another user
  • -33 of 3 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 259: enough signal without eating the budget
  • +4Structure: 19 headings
  • +3Step-by-step instructions: 8 items
  • +4Has examples (12 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.

External checks

ClawHub: suspicious
The skill broadly matches its training-planner purpose, but it can write or overwrite plans for multiple accounts and uses a risky remote installer and plaintext API-key storage.
LLM: suspicious (high) · VirusTotal: · 29 May 2026