Skip to main content
Glama

submit_check_feedback

Dispute a specific check result on a domain's scan (false pass, false fail, wrong details, outdated). Agent-only; requires a solved challenge from get_verification_challenge. Check ids come from get_checks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesThe scanned domain, e.g. stripe.com
reasonYesWhy the check result is wrong
messageYesWhat you observed instead (max 2000 chars)
agent_idYesStable identifier for the reporting agent
check_idYesStable check id being disputed, e.g. access.llms-txt
challenge_idYeschallengeId from get_verification_challenge
challenge_answerYesYour solution to the challenge

TDQS

A4.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It reveals the tool is a write operation (dispute) and requires authentication-like challenge solving. However, it does not disclose side effects, rate limits, or what happens upon success/failure. With no output schema, the agent is left guessing the response.

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 sentences: first sentence states the purpose and accepted dispute types, second sentence lists prerequisites. Every word serves a purpose, with no redundancy or filler.

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?

For a tool with 7 required parameters, no output schema, and no annotations, the description covers the main purpose, acceptable reasons, and prerequisite flows. It is missing the return value or success indication, but given the complexity, it is reasonably complete.

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?

All 7 parameters have schema descriptions (100% coverage). The description adds value by linking check_id and challenge_id/challenge_answer to their source tools (get_checks, get_verification_challenge), which aids the agent in correctly populating them. This goes beyond the schema's static descriptions.

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 ('Dispute a specific check result') and the resource ('a domain's scan'), with explicit types of disputes (false pass, false fail, wrong details, outdated). This distinguishes it from sibling tools like get_checks (retrieval) and submit_feedback (general feedback).

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 prerequisites: 'requires a solved challenge from get_verification_challenge' and 'Check ids come from get_checks.' It also marks itself as 'Agent-only,' giving clear context for when to invoke. It does not explicitly state when not to use, but the guidance is strong.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4/5.0
Disambiguation4/5

Tools are generally well-distinguished, but discover_products and search_capabilities could be confused since both search across domains. The difference in query type (task intent vs. capability) is somewhat subtle. Overall, most tools have clear, separate purposes.

Naming Consistency5/5

All tool names use a consistent verb_noun pattern (e.g., discover_products, get_checks, scan_domain). The naming is predictable and matches the server's domain of evaluating agent-ready properties.

Tool Count5/5

With 11 tools, the server covers scanning, scoring, feedback, and search without being overly broad. Each tool has a distinct role, and the count is appropriate for the focused purpose of assessing agent readiness.

Completeness5/5

The tool set covers the full lifecycle: discover/scan domains, get scores and checks, apply skills, verify with challenges, submit feedback and disputes. There are no obvious missing operations for the stated domain.

Resources