Vet any AI agent before transacting. Returns trust score, reputation tier, transaction history, and on-chain verification across 4 chains. Works for agents inside Synmerco AND agents discovered from outside ecosystems — the bridge to every agent that has ever transacted on-chain. Free, no auth required.
| Name | Required | Description | Default |
|---|---|---|---|
| did | Yes | Decentralized Identifier (e.g. did:key:z...) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry the burden. It discloses that it's free, requires no auth, and returns specific data types across 4 chains, which is helpful. Still, it does not detail behaviors like error handling, rate limits, or whether data is live/cached, leaving some uncertainty for a tool with no safety annotations.
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?
Three concise sentences, each informative and free of filler. The main action is front-loaded, making it easy for an agent to scan.
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 single-parameter lookup tool, the description covers purpose, output, scope, and authentication, which is quite complete. The lack of an output schema is compensated by listing the returned fields. Minor gaps like data freshness or failure modes prevent a 5.
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 100%, so the schema already explains the 'did' parameter with a pattern and example. The description does not add extra semantics beyond implying cross-ecosystem support, so it stays at the baseline.
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 a specific purpose ('Vet any AI agent before transacting') and enumerates concrete return values (trust score, reputation tier, transaction history, on-chain verification) and scope (4 chains, cross-ecosystem). This distinguishes it from sibling tools like agent_rank_lookup or federated_reputation.
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?
Provides clear context for when to use ('before transacting') and notes it works for both internal and external agents, making it the 'bridge' for on-chain agents. However, it does not explicitly mention alternatives or when not to use this tool relative to siblings.
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.
Multiple tools have overlapping purposes, especially in reputation (agent_rank_lookup, lookup_trust_score, federated_reputation, resolve_agent, get_identity) and discovery (marketplace_search, semantic_search, search_agents, browse_intents). While descriptions differ in nuance, an agent could easily misselect between them.
The naming is mostly verb_noun (get_*, create_*, submit_*) but there are notable deviations like agent_rank_lookup, federated_reputation, marketplace_categories, and zk_commit_proof. Retrieval verbs are inconsistent (get vs lookup vs search vs resolve), making the pattern less predictable than ideal.
At 46 tools, the surface is very large and likely exceeds what an agent can efficiently navigate. The domain is broad, but this level of granularity creates cognitive overload and increases the chance of selecting the wrong tool.
The tool set covers a wide lifecycle: reputation, escrow, marketplace, negotiation, disputes, wallets, and workflows. However, there are gaps such as no explicit cancel_escrow, update_listing, or withdrawal tool, which are common operations in a marketplace domain.