Skip to main content
Glama

autonomous_scan

Identifies gaps across all subsystems, checking for missed detections, stale goals, quality regression, expired predictions, prompt health, and rule effectiveness.

Instructions

TRIGGER: Call this periodically or when the system seems to be underperforming. 🔍 Runs the autonomous gap detector across all subsystems. Checks: missed detections, stale goals, quality regression, expired predictions, prompt health, rule effectiveness.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Without annotations, the description carries full burden for behavioral traits. It lists what is checked but does not disclose side effects, state modifications, resource impact, or read-only nature. The information is adequate but not rich.

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

Conciseness5/5

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

The description is extremely concise: two sentences and a bullet list. It front-loads the trigger, immediately informing the agent when to use it. Every sentence earns its place with zero waste.

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

Completeness4/5

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

Given no parameters and an existing output schema, the description provides sufficient context: trigger and scope. It could elaborate on output structure or prerequisites, but the essentials are covered.

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?

There are no parameters, and schema coverage is 100%. The description adds no parameter detail, which is fine. Baseline for 0 parameters is 4, as the schema already fully covers parameter semantics.

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 the tool 'runs the autonomous gap detector across all subsystems' and lists specific checks. It uses a specific verb and resource, and the broad scope distinguishes it from more targeted sibling tools like bias_scan or check_anti_patterns.

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 provides explicit trigger conditions: 'Call this periodically or when the system seems to be underperforming.' It does not mention when not to use or suggest alternatives, but the given guidance is clear and actionable.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Snehgabani/elite-reasoning-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server