canon_entityMap a ticker (AAPL, BRK.B), a CIK, or a company name to one issuer id with every ticker and exchange, plus EDGAR filing locations. Use before joining prices, filings and news so identifiers line up; source is the SEC public ticker file.
| Name | Required | Description | Default |
|---|---|---|---|
| q | Yes | ||
| limit | No |
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?
Annotations already declare readOnlyHint and openWorldHint, so the description only needs to add context. It adds the SEC public ticker file as the source and specifies the output scope, which is useful behavioral context beyond what annotations provide.
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, front-loaded with the action and accepted input forms, with no filler. The second sentence earns its place by explaining when to call the tool and identifying the data source.
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?
For a read-only resolver with no output schema, the description covers accepted inputs, output content, source, and usage timing. Adding explicit no-match or ambiguity behavior would improve it, but that is a minor gap.
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 schema has no parameter descriptions, but the description compensates with concrete examples for q: AAPL, BRK.B, CIK, or company name. The optional limit parameter is not described, though its name and numeric constraints make its effect inferable.
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?
The description uses a specific verb, 'Map', and names the exact inputs and outputs: ticker, CIK, or company name to one issuer id with every ticker/exchange and EDGAR filing locations. This makes the tool clearly distinct from sibling tools like canon_search or canon_batch.
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?
'Use before joining prices, filings and news so identifiers line up' gives concrete guidance on when to invoke this tool. It does not explicitly state exclusions or name alternatives, so it misses the top criterion.
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 has a clearly distinct job: searching, fetching entries, mapping entities, running formulas, batching computations, verifying receipts, citing, listing sites, monitoring changes, and looking up regulatory thresholds. Even the related compute/batch/verify tools are cleanly separated by single vs. batch execution and verification responsibility.
All tools share the canon_ prefix and use lowercase snake_case, which makes the set feel consistent and predictable. However, the suffixes mix bare resource nouns (canon_sites, canon_thresholds, canon_entity) with verb phrases (canon_describe_formula, canon_list_formulas, canon_get_entry), so the naming convention is not perfectly uniform.
Thirteen tools is well within the ideal range for a reference-and-computation API, and each tool covers a distinct capability without redundancy. The count feels proportionate to the breadth of the finance canon domain.
The surface is complete for a read-only reference service: search, entry retrieval, entity resolution, contract lookup, formula inspection, computation, batch execution, receipt verification, citations, change monitoring, site stats, and regulatory thresholds. There are no obvious dead ends or missing core operations.