Skip to main content
Glama

ecosystem_summary_top_n

Generates a ranked markdown table of top repositories in the AI ecosystem, filtered by category and sorted by stars, recency, or scan freshness.

Instructions

Top-N markdown table of ecosystem repos.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nNoNumber of rows (1..100, default 10).
sortNo``stars`` (default), ``pushed_at`` (last commit recency) or ``scan_freshness`` (last_scanned_at recency).stars
authorNoAuthor recorded on the saved report.ecosystem-summarizer
categoryNoOptional category filter (agent-framework / mcp-server / memory-system / skill-system / tooling).
save_reportNoWhen True, persist via report_save with report_type='ecosystem-top-n'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations provided, and the description does not disclose behavioral traits such as side effects (e.g., save_report parameter persists results). The description only states output format without revealing mutation or write behavior.

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

Conciseness3/5

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

The description is a single sentence, which is concise, but it sacrifices clarity and completeness regarding behavior. It is appropriately front-loaded but too brief for a tool with 5 parameters.

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

Completeness3/5

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

Given the presence of an output schema, the description does not need to explain return values. However, for a tool with multiple parameters and many siblings, more context on usage and side effects would improve completeness.

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

Parameters3/5

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

Schema coverage is 100%, and each parameter is well-described in the schema. The description adds no additional meaning beyond the schema, so baseline 3 is appropriate.

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 'Top-N markdown table of ecosystem repos' uses a specific verb ('Top-N markdown table') and resource ('ecosystem repos'), clearly distinguishing it from sibling tools like ecosystem_search or ecosystem_repo_get.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives. Given many sibling ecosystem tools, explicit context on when to choose this tool over others is missing.

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/CronusL-1141/AI-company'

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