Exactly verify a math/finance claim (VERIFY/REFUTE/ABSTAIN) with a counterexample when false. Use before trusting any AI-produced number, sum, percentage, or formula.
| Name | Required | Description | Default |
|---|---|---|---|
| claim | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that the tool returns VERIFY/REFUTE/ABSTAIN and provides counterexamples when false. No annotations are present, so the description carries the full burden. However, it lacks details on processing, side effects (likely read-only), or constraints like input format.
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?
Two sentences that efficiently convey the core purpose, outputs, and usage guidance. No unnecessary words.
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 no output schema, it appropriately describes possible outputs and a counterexample. For a single-parameter tool, it covers the essential context but could specify claim format or error behavior.
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?
The sole parameter (claim) is described only as 'a math/finance claim'. With 0% schema description coverage, the description fails to add meaningful syntax, format, or examples beyond the bare type.
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?
Description clearly states the action (verify), domain (math/finance), possible outputs (VERIFY/REFUTE/ABSTAIN), and use case (before trusting AI-produced numbers). It distinguishes from sibling tools (audit_rows, covenant_rules, diff_rows) by focusing on claim verification.
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?
Explicitly advises using before trusting AI-produced numbers, sums, percentages, or formulas. Does not explicitly list when not to use or alternatives, but the context with sibling tools makes the usage clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct task: auditing spreadsheet integrity, evaluating covenants, comparing versions, and verifying claims. No overlap in functionality.
Three tools use verb_noun pattern (audit_rows, diff_rows, verify_claim). covenant_rules breaks the pattern but is still clear and readable.
4 tools is well-scoped for a specialized server focused on spreadsheet analysis and verification. No extraneous tools.
Coverage is good for auditing and verification tasks. Missing features like data import/export or row editing are not core to the stated purpose, so only a minor gap.
