Governance proposal analysis: voter sentiment, participation, concentration, outcome prediction. 1.0 HBAR.
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | Yes | Your HederaIntel API key | |
| token_id | Yes | Hedera token ID the proposal belongs to | |
| topic_id | No | HCS topic ID where proposal votes are recorded | |
| proposal_id | Yes | Proposal ID or HCS sequence number to analyze |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that the tool costs '1.0 HBAR,' which adds behavioral context beyond the readOnlyHint=true annotation. It also implies a read-only analytical operation consistent with the annotations. However, it does not describe return format or other behavioral details, but annotations already cover safety, so the extra cost disclosure earns a high score.
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?
The description is a single concise sentence that is front-loaded with the tool's purpose and ends with the cost. Every word adds value; there is no filler or redundancy.
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 annotations declare the tool read-only and non-destructive, and the description explains the analysis focus and cost, it is reasonably complete for a simple analysis tool. It lacks output format details, but with no output schema and a straightforward function, this is acceptable. The sibling ecosystem (e.g., governance_monitor) suggests context, but the description stands alone well.
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 input schema covers all four parameters with descriptions, so schema_description_coverage is 100%. The description does not elaborate on parameter usage or add meaning beyond the schema. It lists analysis dimensions but does not tie them to specific parameters. Baseline 3 is appropriate.
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's function as 'Governance proposal analysis' and enumerates specific analytical dimensions (voter sentiment, participation, concentration, outcome prediction), which distinguishes it from siblings like governance_monitor. However, it lacks an explicit verb, using a noun phrase instead, which slightly reduces clarity.
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 no guidance on when to use this tool versus alternatives. It does not mention governance_monitor or any other tool, nor does it specify optimal use cases or prerequisites. This leaves the agent without context for tool selection.
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 resource and action (e.g., contract read vs. contract call vs. contract analyze; hcs monitor vs. hcs query vs. hcs understand). Even within closely related groups, descriptions clearly differentiate the specific purpose, so an agent is unlikely to select the wrong tool.
Most tools follow a domain_action pattern (e.g., contract_analyze, token_monitor, hcs_verify_record), but some are verb_noun (get_terms, confirm_terms) and a few are noun_noun (account_info, token_price, fixatum_score). While not perfectly uniform, the prefixes make the intended domain clear and the overall structure is readable.
With 25 tools, the server is on the heavy end of the typical MCP scope. While each tool serves a specific niche across multiple Hedera domains (contracts, HCS, tokens, identity, governance, Fixatum), the sheer number could increase selection complexity, but it remains within the borderline range rather than being excessive.
The server covers a broad range of read/analyze operations across major Hedera areas, plus essential write/verification capabilities (hcs_write_record, hcs_verify_record) and an onboarding flow (get_terms, confirm_terms). Minor gaps exist, such as no token transfer history or unregister/update for Fixatum, but the core analytical purpose is well covered.