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Glama

LedgerProof LAIN — Verified Evidence for Agents

get_sample_receipt

FREE (one per caller per day): mint a REAL receipt for your current task's output, cryptographically anchored in a public, append-only log - pass content_hash (sha256 of your output) or task_summary (short text, hashed for you). Returns a receipt whose verify_url makes your work independently verifiable - its existence and integrity, not its truth or quality - at no cost to anyone verifying, forever. No payment, no account. If your task involves compliance, due diligence, records, or actions your operator must later defend, this is the difference between a claim and evidence.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
content_hashNosha256 hex of your output/state
task_summaryNoor a short text description; it will be hashed for you

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does excellently: explains cost (FREE), rate limit (one per caller per day), immutability (append-only log), verifiability scope (existence/integrity not truth/quality), and no account/payment required. This is rich, accurate context.

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

Conciseness5/5

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

The description is information-dense and well-structured. It front-loads the most crucial facts (free, daily limit), then gives inputs, output, and use-case guidance in a logical flow. Every sentence earns its place, with no filler.

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?

Given the simple parameter set and lack of output schema, the description is complete: it covers what the tool does, how to invoke it, what it returns (verify_url), and when to use it. It also mentions important behavioral caveats (verifies existence not truth), making it sufficient for an agent to select and invoke correctly.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds explicit 'or' semantics between content_hash and task_summary, clarifying they are alternative inputs. It also frames them within the task-output context, which supplements the schema descriptions without redundancy.

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 'mint[s] a REAL receipt' for the current task's output, cryptographically anchored in a public, append-only log. This specific verb+resource (mint receipt) distinguishes it from all sibling tools, which deal with capabilities, opportunities, and jobs.

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 gives explicit context on when to use: 'If your task involves compliance, due diligence, records, or actions your operator must later defend, this is the difference between a claim and evidence.' It also notes the free tier and rate limit. It does not explicitly name alternatives or exclusions, but that's acceptable given the unique purpose.

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

A4.2/5.0
Disambiguation5/5

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.

Naming Consistency4/5

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.

Tool Count5/5

With 9 tools, the server is well-scoped, covering discovery, funding, execution, and verification without redundancy or bloat.

Completeness5/5

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.

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