canon_contractFetch one Kalshi (ticker) or Polymarket (slug or condition id) contract and return rules text, close time, resolution source and status in one shape. For a paid cross-venue identity check with a snapshot receipt, call GET /v1/contracts/compare over REST.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| venue | 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?
Annotations already provide readOnlyHint and openWorldHint, so the safety profile is covered. The description adds useful behavioral context by naming the returned fields, the accepted identifier forms per venue, and the 'one shape' normalization behavior. It does not discuss errors or staleness, but the annotation coverage lowers the burden.
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, no filler. The core action and output are front-loaded, and the alternative routing is placed second where it belongs. Every clause earns its place.
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 simple read-only two-parameter tool with no output schema, the description is complete: it explains what inputs are accepted, what outputs will appear, and when to use a different endpoint. Nothing essential for invoking the tool correctly is missing.
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?
With schema description coverage at 0%, the description carries the full burden and succeeds: it explains that 'id' is a Kalshi ticker or a Polymarket slug/condition id depending on the venue, and that 'venue' is the selector between them. Both parameters are given meaningful domain semantics beyond the raw schema.
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 opens with a specific verb and resource: 'Fetch one Kalshi (ticker) or Polymarket (slug or condition id) contract' and names the exact returned fields. This makes it immediately distinguishable from the sibling canon_batch, canon_search, and canon_compare alternatives.
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?
It explicitly routes a different need to 'GET /v1/contracts/compare over REST' when a paid cross-venue identity check with snapshot receipt is required. It does not explicitly contrast with all siblings, but the singular 'one contract' and the compare alternative provide clear enough context for most agents.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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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.