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CD zentao

ZenTao Project Management API Integration | 禅道项目管理 API 集成。支持产品、项目、任务、Bug 全生命周期管理。Triggers: 禅道, zentao, 项目管理, 任务, bug

ClawHub Agent Skills author: 张贝 v1.0.1 MIT-0 67 files body ≈ 6 884 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process D 44/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationInfrastructureOperations and projectstype and topics are labelled automatically from the skill text
JSON
Technical rating
C
73/100
safety, quality, tests
Safety 60%
95
Quality 40%
40
Run on models
none yet
Process rating
D
44/100
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

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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 SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 1

✓ No critical or high findings

Medium and low: 1
  • medium Broad scope meta-agent-memory-dump docs/user.md
    Agent memory / workspace files bundled with the skill (1) — likely a workspace dump with personal data or tokens
    docs/user.md

Files scanned: 67. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: ZenTao Project Management API Integration | 禅道项目管理 API 集成。支持产品、项目、… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 6884 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "config"

Process rating: all ten parameters 44/100

  • 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. 25 mutating operations with no state check
  • 40Consistency. Frontmatter name (zentao) differs from the folder (zentao-api-old)
  • 70Execution cost. Instruction body is 6884 tokens
  • 100Tools and files. No external tools needed
  • 100Steps. 4 steps
  • low 11 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)
  • +3Description length 116: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -223 emoji in the instructions: noise for the model
  • -459 reference files, but SKILL.md never points to them: the model will not open them
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +4Structure: 50 headings
  • +3Step-by-step instructions: 4 items
  • +4Has examples (29 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 40.

External checks

ClawHub: suspicious
This is a disclosed ZenTao automation skill, but it handles plaintext credentials, persists reusable sessions locally, and exposes broad create/edit/delete authority over project data with limited safety guidance.
LLM: suspicious (high) · VirusTotal: · 29 May 2026