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DF opentask-client

OpenTask 分布式任务管理系统。查询和管理 OpenClaw 容器的任务。使用场景:(1) 查询待执行任务、获取任务列表、任务详情;(2) 创建任务、开始执行、完成任务、标记失败、重试、取消;(3) 查看今日统计、任务日志;(4) HEARTBEAT 集成任务检查。触发短语:"查询任务"、"获取任务"、"创建任务"、"完成任务"、"opentask"、"任务管理"。

Not recommendedlow grade D
ClawHub Agent Skills author: Andy Tien v1.4.0 MIT-0 3 files body ≈ 1 090 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process F 33/100 · Will not run — weak spots: steps, result and completion, when it triggers

ReferenceInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
D
59/100
safety, quality, tests
Safety 60%
50
Quality 40%
73
Run on models
none yet
Process rating
F
33/100
Will not run
Steps w 15
0
Result and completion w 14
0
Inputs and preconditions w 11
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.

Exfiltration 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 instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

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 · 10

✓ No critical or high findings

Medium and low: 10
  • medium Exfiltration net-credential-use references/api.md:30
    Credential used in a network call (verify the destination is the intended service)
    curl -H "X-Bot-Key: $OPENTASK_API_KEY" "$OPENTASK_HOST/api/tasks"
  • medium Exfiltration net-credential-use references/api.md:50
    Credential used in a network call (verify the destination is the intended service)
    curl -H "X-Bot-Key: $OPENTASK_API_KEY" \
  • medium Exfiltration net-credential-use references/api.md:67
    Credential used in a network call (verify the destination is the intended service)
    curl -H "X-Bot-Key: $OPENTASK_API_KEY" \
  • medium Exfiltration net-credential-use references/api.md:83
    Credential used in a network call (verify the destination is the intended service)
    curl -H "X-Bot-Key: $OPENTASK_API_KEY" \
  • medium Exfiltration net-credential-use references/api.md:109
    Credential used in a network call (verify the destination is the intended service)
    curl -X POST -H "X-Bot-Key: $OPENTASK_API_KEY" \
  • medium Exfiltration net-credential-use SKILL.md:95
    Credential used in a network call (verify the destination is the intended service)
    curl -H "X-Bot-Key: $OPENTASK_API_KEY" \
  • medium Exfiltration net-credential-use SKILL.md:104
    Credential used in a network call (verify the destination is the intended service)
    curl -X POST -H "X-Bot-Key: $OPENTASK_API_KEY" \
  • medium Exfiltration net-credential-use SKILL.md:113
    Credential used in a network call (verify the destination is the intended service)
    curl -X PUT -H "X-Bot-Key: $OPENTASK_API_KEY" \
  • medium Exfiltration net-credential-use SKILL.md:120
    Credential used in a network call (verify the destination is the intended service)
    curl -X PUT -H "X-Bot-Key: $OPENTASK_API_KEY" \
  • medium Exfiltration net-credential-use SKILL.md:139
    Credential used in a network call (verify the destination is the intended service)
    curl -s -H "X-Bot-Key: $OPENTASK_API_KEY" \

Files scanned: 3. 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 33/100

  • 0Steps. Prose only: no discrete steps
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1090 tokens
  • 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)
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 187: enough signal without eating the budget
  • +4Structure: 22 headings
  • +4Has examples (12 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.

External checks

ClawHub: suspicious
This is a coherent OpenTask client, but it can let a configured remote task queue influence agent work and mutate task state without enough scoping or approval guidance.
LLM: suspicious (high) · VirusTotal: · 29 May 2026