Hesper Atlas Evidence

Methodology and calculation provenance

get_provenance

Read-onlyIdempotent

Use when a user asks where a number came from, whether two results used the same code, or what first-party hashes can and cannot prove. Returns the authoritative public methodology version, content-derived published-decision and evaluation-pipeline calculation versions, component SHA-256 hashes, canonicalization rule and attestation limitations. Use it to determine whether two figures came from the same rules/code. It explicitly states that no independent timestamp authority or third-party signer is configured.

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Output Schema

TableJSON Schema

Name	Required	Description	Default
`as_of`	No
`source`	No
`caveats`	No
`is_live`	No
`citation`	No
`data_type`	No
`disclaimer`	Yes
`provenance`	No
`source_url`	No
`last_updated`	No
`calculation_version`	No
`methodology_version`	No

TDQS

A4.7/5.0

Behavior5/5

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

Annotations already cover read-only and idempotent behavior. The description adds important non-obvious behavioral context: 'it explicitly states that no independent timestamp authority or third-party signer is configured' and clarifies what first-party hashes can and cannot prove. This goes well beyond the structured annotations.

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 front-loaded with the exact user intents it serves, followed by the concrete data returned, and ends with a key limitation. Every sentence contributes useful information without redundancy.

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?

For a parameterless, read-only tool with a rich output schema and annotations, the description fully covers purpose, use cases, return content, and the main limitation. Nothing needed for correct invocation is missing.

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?

The tool has zero parameters, so schema coverage is 100% and there are no parameter semantics to explain. The description focuses on return content rather than inputs, which is appropriate for a parameterless tool.

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 opens with specific use cases: 'where a number came from, whether two results used the same code, or what first-party hashes can and cannot prove'. It names the resource (methodology and calculation provenance) and distinguishes itself from siblings like get_methodology by emphasizing hashes, calculation versions, and attestation limitations.

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?

Explicit 'Use when' conditions are provided for determining number provenance and code consistency. It does not explicitly state when not to use the tool or mention sibling alternatives, but the usage context is clear enough for an agent to select it correctly.

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

A4/5.0

Disambiguation3/5

The five historical-performance tools (get_track_record, get_walk_forward_evidence, get_heldout_evidence, get_ledger_stats, list_closed_trades) occupy heavily overlapping territory, and an agent could easily grab the wrong evidence artifact. The detailed 'use when' openers help considerably, but the boundaries between replay, walk-forward, and validation are subtle enough that misselection risk remains real.

Naming Consistency4/5

All tools follow a clean snake_case verb_noun pattern, with get_ reserved for single artifacts/reports and list_ for enumerable collections. The convention is slightly loose—get_changes_since and get_ledger_stats are more list-like than get_-like, and the verbs don't always signal collection size—but overall the pattern is predictable and readable.

Tool Count4/5

At 15 tools, the server sits at the upper boundary of a well-scoped surface, and each tool does earn its place in the evidence ecosystem (current signal, lists, portfolio, context, diffs, publications, replay, validation, methodology, provenance). It is slightly heavy and could feel daunting, but nothing is redundant.

Completeness4/5

The surface covers the evidence domain thoroughly: current state, forward publication history, performance replays, two distinct validation artifacts, methodology, and hash-level provenance. Minor gaps exist—there is no tool to enumerate the full covered universe or search across tickers, forcing users to arrive with a symbol in mind—but core workflows have no dead ends.

Resources

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