List everything the LedgerProof Autonomous Network (LAIN) offers: capability ids (receipt.agent-run, evidence.verify, answer.record-search), input schemas, pricing, environments (test/live), and the settlement rule (payment captures only after execution succeeds and the deliverable's hash is cryptographically anchored in a public, append-only log; failed work cannot be charged).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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?
With no annotations, the description carries the burden of behavioral disclosure. It goes beyond a simple list by explaining the settlement rule: payment is captured only after successful execution and cryptographic anchoring, and failed work cannot be charged. This is valuable context about the tool's behavior, though it does not explicitly state that the tool itself is read-only.
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 dense sentence with a colon leading into a list of items. Every component adds value, but it could be broken into smaller sentences for improved readability. It is sufficiently front-loaded with the verb 'List' and resource.
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 absence of annotations and output schema, this description is the sole source of context. It thoroughly covers what the tool returns (capability ids, schemas, pricing, environments) and includes the crucial settlement rule, making it comprehensive for an agent to understand the tool's purpose and expectations.
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 tool has 0 parameters, so the schema is trivially covered. The description adds no parameter details because there are none; the baseline for 0 parameters is 4, which is appropriate here.
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 verb 'List' and the resource 'everything the LedgerProof Autonomous Network (LAIN) offers', enumerating specific items such as capability ids, input schemas, pricing, and environments. It distinguishes this tool from siblings like discover_opportunities by focusing on capabilities rather than opportunities.
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 usage is implied: to learn about LAIN's offerings, one should use this tool. However, there is no explicit statement of when to use it versus alternatives like discover_opportunities, nor any exclusions or conditions.
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 operation—discovery, funding, job polling, receipt minting, capability purchase, confidence resolution, graph reading, and verification. No two tools overlap in purpose, and the detailed descriptions make selection unambiguous.
Most tools follow a verb_noun pattern (discover_*, fund_opportunity, get_job, get_sample_receipt, request_capability, resolve_confidence), but subject_evidence_graph is a noun phrase and verify is a bare verb, creating minor inconsistency.
With 9 tools, the server is well-scoped, covering discovery, funding, execution, and verification without redundancy or bloat.
The tool surface covers the full evidence lifecycle: discover opportunities, fund them, poll jobs, mint receipts, request capabilities, resolve confidence gaps, read evidence graphs, and verify receipts. No obvious operational gaps.
