Skill flagged — suspicious patterns detected

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agent-task-manager

v1.0.2

Manages multi-step, stateful agent workflows with task dependencies, persistent state, error recovery, and external API rate-limit handling using SkillBoss A...

0· 57·0 current·0 all-time
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
Capability signals
Requires sensitive credentials
These labels describe what authority the skill may exercise. They are separate from suspicious or malicious moderation verdicts.
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Suspicious
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Suspicious
medium confidence
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Purpose & Capability
The skill's code and SKILL.md consistently call https://api.skillboss.co/v1/pilot using an environment variable SKILLBOSS_API_KEY, which is coherent with the stated purpose (SkillBoss-backed orchestration). However, the registry metadata lists no required env vars or dependencies; that's inconsistent and misleading (the skill will fail or raise KeyError without SKILLBOSS_API_KEY).
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Instruction Scope
SKILL.md and the Python scripts instruct the agent to call the SkillBoss API for parsing, LLM inference, and notifications, and to read/write local state files (task_state.json, agent_task_manager_data/*). That scope matches the description, but the instructions access an environment secret (SKILLBOSS_API_KEY) that the registry did not declare — the instructions therefore reference runtime secrets not advertised in metadata.
Install Mechanism
No install spec (instruction-only install). All code is included in the skill bundle; no external downloads or extract steps are specified. This is low-install-risk, but it does mean the included Python scripts will run as-is in the agent environment.
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Credentials
The only credential used is SKILLBOSS_API_KEY (appropriate for the SkillBoss integration). However: (1) the registry metadata did not declare this required env var, (2) the code will transmit task contents and any parsed user inputs to SkillBoss, which may include sensitive data, and (3) Python dependency 'requests' is used but not declared in metadata. These omissions reduce transparency and raise the chance of accidental secret exposure or runtime failure.
Persistence & Privilege
The skill persists state locally (task_state.json) and creates a timestamp directory ./agent_task_manager_data for cooldowns. It does not request always:true or system-wide config changes and does not modify other skills. This local persistence is proportional to its purpose but operators should be aware that files are created in the working directory and may contain task data.
What to consider before installing
This skill appears to implement the advertised orchestration and SkillBoss integration, but there are important inconsistencies to address before installing: - The code and SKILL.md require SKILLBOSS_API_KEY (os.environ["SKILLBOSS_API_KEY"]) but the registry metadata lists no required env vars. Expect to provide a SkillBoss API key; otherwise the scripts will error. - The Python scripts use the requests library but the skill does not declare dependencies. Ensure your environment has Python 3 and the required packages installed (e.g., pip install requests) before running. - The skill will send parsed human requests, workflow definitions, and any task data to api.skillboss.co. Do not provide sensitive secrets or private data in tasks unless you trust SkillBoss and understand the API key's permissions and retention policy. - The skill writes task_state.json and ./agent_task_manager_data/*. If you run it in a shared environment, consider running in an isolated directory or container to avoid leaking task content. - Source and homepage are unknown. If you need higher assurance, request or verify the publisher identity, check for signed releases, or review the included code yourself. If you cannot verify provenance, run in a sandbox and limit the SKILLBOSS_API_KEY scope (rotate/delete the key after testing). Given these mismatches (undeclared env var and undeclared dependency), treat the skill as suspicious until the author or registry metadata is corrected and you confirm the runtime behavior in a safe environment.

Like a lobster shell, security has layers — review code before you run it.

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License

MIT-0
Free to use, modify, and redistribute. No attribution required.

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