scan_slack

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

The description thoroughly discloses behavioral traits: non-modification of Slack, side effect of uploading reports and optionally encrypted secrets, auth requirements, redaction of raw secrets, and subject to Slack API rate limits. This adds substantial value beyond annotations (which indicate non-read-only, non-destructive, open-world). No contradiction with annotations.

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

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

The description is fairly concise with 6 sentences, each delivering key information: purpose, safety, auth, side effects, output behavior, and rate limits. It is front-loaded with the main action. Minor redundancy (auth details already in schema) but overall efficient.

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

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

Given the tool's complexity (7 params, output schema, multiple side effects), the description covers purpose, auth, side effects, output redaction, and rate limits. It does not explain the output schema but that is separate. The description is complete enough for an AI agent to select and invoke correctly.

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

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

Schema coverage is 100% with good descriptions. The tool description adds extra context: mentions that api_key can also be set via environment variable (schema says same), that ai_analysis requires n0s1 Pro (schema lacks that), and overall side effects. While parameters are well-documented, the description does not detail each one but provides overarching context that aids understanding.

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

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

The description clearly states the verb 'Read Slack messages to detect leaked secrets' and resource 'Slack messages'. It explicitly distinguishes from sibling scan tools by focusing on Slack platform and emphasizes non-modification: 'Never modifies Slack — no messages are posted or edited.'

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

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

The description provides clear context for when to use the tool (detecting secrets in Slack), auth requirements (bot token with specific scopes, env var or api_key), and side effects (upload to n0s1 backend). It does not explicitly state when not to use or name alternatives, but the sibling tools are for different platforms so it's clear this is for Slack only.

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