Skip to main content
Glama

trust_endorse

Boost an agent's social trust score by endorsing them. Requires a registered endorser; self-endorsements are rejected.

Instructions

Endorse an agent to boost their social trust score. Endorser must be a registered agent. Self-endorsements are rejected.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
commentNoEndorsement comment (optional)
agent_idYesAgent UUID to endorse
endorser_idYesYour agent UUID or pubkey
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses two behavioral constraints (must be registered, self-endorsements rejected) but does not mention side effects, success/failure return values, or any other system behavior. The description adds some value but leaves significant behavioral aspects undisclosed.

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 two concise, front-loaded sentences with no wasted words. It immediately states the core action and then adds key constraints, making it highly scannable and efficient.

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 tool's simplicity, the description covers the main purpose and constraints, but with no output schema and no annotations, it does not explain what happens on success or failure. While it is adequate for a basic operation, it could be more complete by mentioning the expected result or postconditions.

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?

The schema already provides complete descriptions for all 3 parameters (100% coverage), so the baseline is 3. The description adds marginal context by clarifying that the endorser must be a registered agent, which slightly elaborates on the endorser_id field, but does not fundamentally enhance parameter understanding.

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 action ('Endorse an agent') and the purpose ('to boost their social trust score'), using a specific verb and resource. This distinguishes it from sibling tools like trust_lookup or trust_review, which focus on reading or reviewing rather than endorsing.

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

Usage Guidelines3/5

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

The description implies usage (endorsing an agent) and provides concrete prerequisites (endorser must be registered, self-endorsements rejected). However, it does not explicitly mention when to use this tool over alternatives or provide any exclusions, leaving some ambiguity in selection among the trust-related siblings.

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/Schmoll86/trust-mcp'

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