workspace_summaryOutcome, model and policy counts across your recent receipts. Requires your aqta_ key.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many recent receipts to summarise, default 100. |
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?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds the behavioral requirement of an 'aqta_ key', which is not in the annotations, increasing transparency. However, it does not discuss rate limits, response format, or error handling.
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?
Two sentences, front-loaded with the purpose. No redundant information. Every word earns its place.
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 simple tool with one parameter, no output schema, and annotations covering safety, the description is quite complete. It specifies the output type (counts of three dimensions), the input scope (recent receipts), and a prerequisite. It could mention the output format or default behavior, but it is adequate for effective use.
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% for the single parameter 'limit' with a description in the schema. The description adds context about what is being summarized (outcome, model, policy counts) but does not provide additional semantics for the 'limit' parameter beyond what the schema already states. Baseline of 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 verb 'summarise' and the resource 'workspace decisions' via 'Outcome, model and policy counts across your recent receipts.' It distinguishes itself from sibling tools like 'list_my_receipts' (lists) and 'decode_receipt' (decodes) by focusing on aggregation counts.
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 mentions a prerequisite ('Requires your aqta_ key') but provides no guidance on when to use this tool versus alternatives like 'list_my_receipts' or 'get_review_pack'. There is no explicit exclusion or usage context beyond the tool's purpose.
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.
Most tools have clear distinct jobs: decode, verify, get, list, summarize. The only mildly overlapping pairs are decode_receipt vs explain_attestation_format and verify_receipt vs verify_evidence_pack, but the scopes are well described.
The dominant pattern is verb_noun: decode_receipt, get_public_key, list_my_receipts, verify_receipt. workspace_summary breaks the pattern by being noun-only, but the rest are consistent enough to be predictable.
10 tools is well within the ideal range for a focused attestation and receipt-verification server. Each tool serves a distinct operation from fetching samples and keys to decoding, verifying, listing, and summarizing receipts.
The read/verify workflow is well covered: format explanation, decoding, single-receipt verification, pack verification, sample artifacts, workspace listing, and summary. The main gap is that transparency proofs can be retrieved but there is no corresponding tool for independently verifying a transparency proof.