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periscope_system

Check system status, apply updates, and retrieve the agent guide.

Instructions

Install status, self-update, and the current agent guide — Periscope's self-maintenance tool. action='status' (read-only): running version vs on-disk version, git commit, install type, capabilities (Node/Lighthouse, display for headed, Chromium), active session count, and whether an update is available. action='agents_md' (read-only): returns the CURRENT AGENTS.md so you can refresh a stale pasted copy of your operating guide. action='update': dry-run by default (commits behind + incoming changes); apply=true runs the updater (git pull + deps, data/ untouched) — new code loads only after the MCP server restarts, and the response says so explicitly. Managed installs (Docker, no .git) refuse update with guidance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
applyNoFor action='update': actually run the update instead of the dry-run check (default: false)
forceNoFor action='update' with apply=true: auto-stash local modifications first (update.sh --force)
actionNostatus = install/version/capabilities report (default); update = check or apply an update; agents_md = fetch the current agent guide
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It thoroughly describes behavior: 'status' and 'agents_md' are read-only, 'update' is dry-run by default, apply=true runs updater but new code loads only after restart, and managed installs refuse update with guidance. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is fairly long but well-structured: a summary sentence followed by bullet points for each action. It is front-loaded and contains no unnecessary details. Slightly verbose but efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description compensates by explaining return values for 'status' (version, capabilities, etc.) and 'agents_md', and the behavior for 'update'. It covers all three parameters and is complete for a system maintenance tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% (baseline 3), but the description adds value by explaining each action's behavior and the context for 'apply' and 'force' parameters. For example, it clarifies that 'apply' defaults to false and 'force' is for auto-stashing modifications.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it is a self-maintenance tool for install status, self-update, and fetching the agent guide. It lists three distinct actions ('status', 'agents_md', 'update') each with specific details, making it distinct from sibling tools which are all about testing and web interaction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for maintenance tasks such as checking version, updating, or refreshing the agent guide. It does not explicitly state when not to use or compare to alternatives, but the context of sibling tools makes the use case clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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