quantifyme

Get Deploy Result

get_deploy_result

Read-onlyIdempotent

Wait for a one_shot deploy to finish and return its final result.

`one_shot` returns a job_token immediately and the LIVE CARD already streams
progress and renders the interactive backtest chart itself. Call this ONCE with
the token to get the final numbers as TEXT so you can summarize them — it does
NOT render another card (no need for get_model_chart). It BLOCKS until the deploy
finishes (or ~2.5 min); on timeout it returns ok:false + pending:true — call it
again with the same token.

IMPORTANT: if `source == "community"`, the deploy used a PRE-EXISTING strategy by
`@author` (the user picked it) - tell the user that, share the `live_url` as the
Live dashboard link, and ask whether they'd like to GENERATE A CUSTOM strategy
instead. A `suggestion` is a community strategy that matched a vague request; it
was NOT deployed; offer it, and deploy it only after the user sees its author and
code and picks it. Use the `note` field as your guide.

Args:
  job_token: the token returned by `one_shot`.

Returns:
  dict with: ok, stem, model, live_url, symbol, timeframe, channels (list),
  stats:{ret, wr, pf, n, mdd} (out-of-sample test-split metrics — SHOW THESE),
  source ("preset" | "generated" | "community"), author (community username if
  any), author_url + strategy_url (render @author and "pre-existing strategy" as
  those Markdown links), community_id, suggest_custom (bool), suggestion
  ({community_id, title, author} or null: offered, not deployed), and note (a
  ready instruction - follow it). On failure: {ok:false, error} (or {pending:true}).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`job_token`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

AddedMay 23, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Goes well beyond the annotations: discloses that the call BLOCKS up to ~2.5 minutes, the exact timeout failure shape, the safe retry semantics with the same token, and that no additional card is rendered. This is consistent with readOnlyHint=true and idempotentHint=true rather than contradicting them.

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?

Purpose and blocking behavior are front-loaded and the Returns block is well structured. The community/suggestion handling is several sentences of workflow policy that could be trimmed, but each sentence does drive correct agent behavior rather than restating the schema.

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?

Covers the blocking/timeout contract, the retry protocol, the full return shape semantics, and the source-dependent user-facing behavior. Even though an output schema exists, the field-level meaning (which stats to show, how to render author/strategy links) adds required interpretation.

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?

Schema coverage is 0% for the single job_token parameter, so the schema contributes nothing. The description compensates by naming its origin ('the token returned by one_shot'), but adds no detail on format, expiry, or reuse constraints beyond the retry note.

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?

States a specific verb and resource ('wait for a one_shot deploy to finish and return its final result') and explicitly distinguishes itself from the sibling get_model_chart ('it does NOT render another card'). An agent can tell exactly what this returns and what it is not for.

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

Usage Guidelines5/5

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

Explicit call-count guidance ('call this ONCE'), the condition under which it is needed, and the retry path ('on timeout it returns ok:false + pending:true — call it again with the same token'). It also gives conditional handling for source=='community' and for suggestions, including the when-not-to-deploy rule.

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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