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Glama

Hesper Atlas Evidence

Current end-of-day signal (subscription)

get_signal
Read-onlyIdempotent

Use when an authorized user asks for the latest Hesper Atlas action on one ticker; do not substitute replay data if access is missing. Returns the latest completed end-of-day state: the bot-safe action and target position, confirmed engine ownership state, conviction score, both the published current leg and longer-history first entry, trend extension, relative strength, fundamental health grade, valuation rating, sell-risk level and the trade-plan trigger prices. action and suggested_position are authoritative when a trigger has been crossed. Requires an active Hesper Atlas subscription. Signal data, not investment advice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesTicker symbol, e.g. NVDA. Case-insensitive.

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

A4.4/5.0
Behavior5/5

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

Annotations already mark the tool as readOnly, idempotent, and non-destructive. The description adds substantial behavior beyond that: it requires an active Hesper Atlas subscription, returns only the latest completed end-of-day state, and explains that `action` and `suggested_position` are authoritative once a trigger is crossed. It also includes the 'signal data, not investment advice' caveat.

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

Conciseness4/5

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

The description is dense but structured: a front-loaded usage directive, a colon-introduced list of return fields, and concise caveats. Every sentence adds information; the field list is arguably long but necessary given the tool's specificity.

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 single-parameter, read-only tool with an output schema and annotations, this description is complete. It covers when to use it, subscription requirements, what data is returned, field authority semantics, and a legal disclaimer. Nothing essential 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?

The input schema fully documents the single `symbol` parameter with a description, example, and case-insensitivity note (100% schema coverage). The tool description adds no new parameter-level detail beyond referring to 'one ticker', which matches the baseline expectation for a fully covered schema.

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 use case ('Use when an authorized user asks for the latest Hesper Atlas action on one ticker') and names the exact resource ('latest completed end-of-day state'). It clearly distinguishes itself from replay data and subsequent sibling tools by scoping to a single ticker and the current signal.

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 a clear when-to-use condition (authorized user, latest action, one ticker) and explicitly instructs not to substitute replay data if access is missing. It mentions the subscription prerequisite, but does not explicitly name sibling alternatives such as list_signals or get_symbol_record, so it stops just short of full alternative routing.

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