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Hesper Atlas Evidence

Forward publication commitments

list_forward_publications
Read-onlyIdempotent

Use when a user asks what Hesper Atlas actually published, when it was committed, what changed, or whether forward history is mature enough to evaluate. Returns public append-only manifests for end-of-day signal publications: stable publication id, publication time, market-data as-of date, scan schema, record counts, previous-publication link and a SHA-256 commitment over the exact frozen agent-facing signal rows. A compact summary separates snapshot revisions from distinct market dates and explicitly refuses to calculate performance from commitments. The manifests prove what was committed without exposing the paid current signal book. The ledger begins at deployment; there is no fabricated historical backfill. Signal data, not investment advice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNewest manifests to return, default 30.
since_as_ofNoOnly snapshots on or after YYYY-MM-DD.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
as_ofNo
sourceNo
caveatsNo
is_liveNo
citationNo
data_typeNo
disclaimerYes
provenanceNo
source_urlNo
last_updatedNo
calculation_versionNo
methodology_versionNo

TDQS

A4.5/5.0
Behavior5/5

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

The description goes well beyond the readOnly/idempotent annotations by revealing append-only semantics, the refusal to calculate performance from commitments, the absence of fabricated historical backfill, and the boundary that paid current signal data is not exposed. These are meaningful behavioral traits an agent needs to set expectations correctly.

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 a 'Use when' trigger, then packs precise, non-redundant details about return contents and behavioral guarantees. The final disclaimer is short and earns its place by preventing misuse. No sentence is wasted.

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 two optional parameters, an output schema, and read-only annotations, the description is complete: it explains what is returned, what is intentionally not computed, the ledger's history boundary, and how to decide when to call it. Nothing critical for correct invocation or expectation-setting is missing.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents 'limit' and 'since_as_of' with clear meanings. The description adds context about manifests and the ledger but does not directly elaborate on parameter usage, which matches the baseline of 3 for high schema coverage.

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 a specific set of user intents ('what Hesper Atlas actually published, when it was committed, what changed, or whether forward history is mature enough to evaluate') and then names the exact deliverable: public append-only manifests for end-of-day signal publications. It also distinguishes itself from sibling signal/list tools by emphasizing that it proves commitments without exposing the paid current signal book.

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 explicitly says 'Use when a user asks...' and lists four concrete triggering conditions, making the appropriate invocation context clear. It does not name alternative sibling tools or state when not to use this tool, so it stops short of a full 5.

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