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audit_agent_readiness

Read-only

RECOMPUTABLE agent-readiness audit of any agent URL: scores 0-100 + grade on handshake readiness (/.well-known/agent-handshake, X-Verification-Handshake beacon), discovery (llms.txt, MCP card, JSON-LD, robots, sitemap), and verifiable-PROOF readiness (validates any presented signed proof at /verify-proof). Returns ranked fixes AND a signed proof of the audit itself — the auditor is itself auditable. Every result re-derives from a public fetch.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe agent endpoint/site URL to audit (public http(s) only)

TDQS

A4.4/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the readOnlyHint and openWorldHint annotations, the description discloses that results are recomputable from public fetches, that it validates signed proofs at /verify-proof, and that it returns a signed proof of the audit itself. This gives substantial insight into side effects and trust properties not available in annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences with the first being dense but information-packed. It front-loads the core purpose and lists key audit dimensions. The last sentence about public fetch is slightly redundant with 'RECOMPUTABLE' but still adds clarity. Generally efficient with no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite lacking an output schema, the description adequately explains return values: score 0-100, grade, ranked fixes, and signed proof. It also covers the audit categories and the validation of external proofs. For a single-parameter tool, this is complete enough for an agent to understand the tool's behavior and outputs.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with the url parameter already described as 'public http(s) only'. The description adds 'any agent URL', which is similar but does not provide additional format, examples, or constraints beyond what the schema already states. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs an agent-readiness audit of any agent URL, listing specific checks (handshake, discovery, proof) and outputs (score, grade, fixes, signed proof). This distinguishes it from siblings like verify_proof which focus on proof verification, and browse which is a generic fetch.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context: use this to audit any public agent URL for readiness. However, it does not explicitly mention alternatives or when not to use it, such as differentiating from verify_proof or conformance_certify. The audience is implied, but exclusions are absent.

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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TDQS

A3.6/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but there is potential confusion between 'decision' and 'reason', both offering advisory output. Also, 'review', 'witness', 'prove', and 'verify_proof' overlap in the proofs space, though descriptions differentiate them. Overall, an agent can disambiguate with careful reading.

Naming Consistency4/5

All tool names use lowercase and underscores (snake_case), which is consistent. However, the verbs vary: some are imperative (e.g., 'browse', 'execute'), while others are nouns (e.g., 'signals', 'ledger'), breaking a strict verb_noun pattern. Overall, the naming is readable and mostly predictable.

Tool Count2/5

With 30 tools, the surface is too large for a well-scoped server. Many functions could be separated (e.g., memory, workspace, feedback, marketplace). This excess makes it harder for an agent to navigate and select the right tool quickly.

Completeness3/5

The tool set covers core CRUD for memory and workspace, plus feedback, marketplace purchase, bounties, and verification. However, there is no tool to list or search marketplace listings, and workspace creation is only implicit via 'execute'. These gaps hinder fluid workflows.