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Glama

agent-compute-ledger

list_entries

List all ledger entries for an agent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. First observed

TDQS

B3.2/5.0
Behavior2/5

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

There are no annotations, so the description carries the full burden of disclosing behavior. It states 'list all ledger entries' which implies a read operation, but it does not mention ordering, pagination, read-only safety, or any side effects or requirements. The terse text adds minimal behavioral insight beyond the name.

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 a single, focused sentence with no filler words. It is easily scannable and front-loaded with the core action.

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

Completeness3/5

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

The tool is simple and has an output schema, so return values are defined elsewhere. The description covers what it does and who it targets, but lacks usage context and any caveats. It is minimally viable but not comprehensive.

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

Parameters2/5

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

The schema has zero description coverage for agent_id, and the description only implies its role via 'for an agent'. It does not explain the format, constraints, or relationship to the ledger entries, so the parameter's semantics are under-specified.

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 uses a specific verb 'list' and resource 'ledger entries' with a clear scope 'for an agent', making the tool's purpose immediately obvious. It distinguishes itself from siblings like list_inventories by naming the unique resource (ledger entries).

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool vs alternatives such as list_inventories or get_inventory. The description gives no context about prerequisites, exclusions, or typical use cases, leaving the agent to infer usage.

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

B3.3/5.0
Disambiguation4/5

Most tools have clearly distinct purposes: recording work, recording inventory, listing, verifying, and attesting. 'attest' and 'carbon_receipt' are somewhat related but serve different functions (general attestation vs. carbon-specific receipt), so they are not easily confused.

Naming Consistency3/5

The majority follow a verb_noun pattern (record_work, list_entries, verify_chain), but 'carbon_receipt' and 'footprint' are noun-only, and 'attest' is verb-only. This slight inconsistency in verb usage makes the pattern less predictable.

Tool Count5/5

With 12 tools, the server is well-scoped for a compute ledger and carbon accounting domain. Each tool covers a distinct concern—recording, querying, verifying, and summarizing—without redundancy.

Completeness5/5

The surface covers the full lifecycle: recording compute work and inventory, retrieving and listing data, verifying chains and attestations, and generating summaries. No obvious gaps exist for the stated domain.