form_d_latest_offering_statesReturn only the latest filing state from each amendment-aware Form D chain for an issuer. This is a normalized regulatory snapshot, not proof that the amount sold closed or that separate chains are economically distinct rounds.
| Name | Required | Description | Default |
|---|---|---|---|
| cik | Yes | ||
| limit | No |
| Name | Required | Description | Default |
|---|---|---|---|
| returned | Yes | ||
| offerings | 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 declare readOnlyHint=true and destructiveHint=false, so the description adds value by explaining the data's nature as a 'normalized regulatory snapshot' and its limitations. This provides context beyond the annotations without contradicting them.
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 with zero waste: the first clearly states the core function, the second adds crucial behavioral caveats. Every word earns its place, making it highly efficient and front-loaded.
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 the output schema exists and annotations cover safety and idempotence, the description provides sufficient behavioral context for a normalized regulatory snapshot. The only gap is parameter documentation, but the tool is simple (cik and limit), so overall completeness is high.
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?
Schema coverage is 0% and the description does not explain the parameters cik or limit. The description only implies that it works per issuer, but does not specify the meaning or range of limit. Without compensation from the description, agents lack clarity on parameter semantics.
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 clearly states the tool returns the latest filing state per amendment-aware Form D chain for an issuer, using specific verbs and nouns. It also distinguishes itself from siblings by emphasizing 'normalized regulatory snapshot' and clarifying what it does not prove, effectively differentiating from related tools like form_d_amendment_chains.
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?
The description provides important caveats about interpretation ('not proof that the amount sold closed') but does not explicitly state when to use this tool versus alternatives. It implies usage for obtaining latest states per chain but lacks explicit when-not-to-use guidance or sibling comparisons.
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.
Many tools have overlapping purposes, e.g., ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded all route questions to data sources with minor differences. Form D tools and meta-tools (discover_tools, suggest_questions) further blur boundaries, making it hard for an agent to select the right tool.
Most tools follow a consistent snake_case verb_noun pattern (e.g., resolve_entity, validate_claim, subscribe). However, there are minor deviations like bet_research and deep_research without clear verbs, and the ask_pipeworx variants use irregular suffixes.
With 39 tools, the server is over-scoped, including many utility and meta-tools (remember, recall, forget, list_subscriptions) that inflate the count beyond the core domain (SEC Form D and data lookups). A more focused set of 10-15 tools would be more coherent.
The tool set covers a very broad range of data sources and actions, including SEC filings, prediction markets, entity profiling, and AI visibility. However, the completeness is uneven; for example, there are many Form D tools but few for other SEC forms, and some areas like weather or clinical trials are only accessible via ask_pipeworx.