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Stocklake — AI Stock Intelligence

by dev.stocklake
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Get Market News Feed

get_news_feed
Read-onlyIdempotent

Most notable recent news across all tracked stocks: a market-wide briefing. Unlike get_stock_news (one symbol), this scans every tracked stock and returns articles ranked by signal_score, newest first within each score.

Use this for:

  • Morning briefing: "what happened in the market this week?"

  • Catalyst scanning: "what news is driving moves right now?"

  • Event monitoring: "which stocks have high-impact news today?"

  • min_signal_score: minimum signal_score (0-100, default 60).

  • days: look-back window in days (default 3, max 10).

  • limit: max articles returned (default 10, max 25).

  • Per article: symbol, title, published_at, ai_sentiment, ai_summary, signal_score (0-100), signal_score_band (Weak/Moderate/Strong/Very Strong).

  • signal_score is the symbol's current news-based signal score when one was raised in the last 90 days (the same number get_stock_news() and get_signals() report), otherwise a score computed from the article's own classification. It is always a single number.

  • collapsed_count: present when several articles reported the same event; only the highest-ranked one is returned and this says how many were merged into it. limit counts distinct events.

Articles are published by third parties; titles and summaries describe what those articles say. Requires a Pro account. For informational purposes only. Not financial advice.

Input Schema

NameRequiredDescriptionDefault
daysNoLook-back window in days (default 3, max 10).
limitNoMax articles returned (default 10, max 25).
min_signal_scoreNoMinimum signal_score, 0-100 (default 60).

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / min_signal_score / description
      Previous value: -"Minimum signal_score used to SELECT articles server-side, 0-100 (default 60). Resolved per-article (this symbol's live signal_score if one exists, else a per-article magnitude computed from sentiment/confidence/flag_score) since a live signal doesn't exist for every article."New value: +"Minimum signal_score, 0-100 (default 60)."
  2. Changed1 schema field changed
    • changedInput schema / properties / min_signal_score / description
      Previous value: -"Minimum news_score used to SELECT articles server-side, 0-100 (default 60) — same 0-100 scale/bands as signal_score. Resolved per-article (stored value preferred, computed via the sentiment/confidence/flag_score fallback formula otherwise) since news_score is stored on only a fraction of articles today."New value: +"Minimum signal_score used to SELECT articles server-side, 0-100 (default 60). Resolved per-article (this symbol's live signal_score if one exists, else a per-article magnitude computed from sentiment/confidence/flag_score) since a live signal doesn't exist for every article."
  3. Changed3 schema fields changed
    • addedInput schema / properties / days / description
      Added value: +"Look-back window in days (default 3, max 10)."
    • addedInput schema / properties / limit / description
      Added value: +"Max articles returned (default 10, max 25)."
    • addedInput schema / properties / min_signal_score / description
      Added value: +"Minimum news_score used to SELECT articles server-side, 0-100 (default 60) — same 0-100 scale/bands as signal_score. Resolved per-article (stored value preferred, computed via the sentiment/confidence/flag_score fallback formula otherwise) since news_score is stored on only a fraction of articles today."
  4. Changed2 schema fields changed
    • removedInput schema / properties / min_flag_score
      Removed value: -{
-  "default": 8,
-  "type": "integer"
-}
    • addedInput schema / properties / min_signal_score
      Added value: +{
+  "default": 60,
+  "type": "integer"
+}
  5. Added

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare the safety profile (readOnlyHint, idempotentHint, destructiveHint false). The description adds valuable context beyond that: a Pro account requirement, third-party content provenance ('articles are published by third parties'), and a disclaimer, plus dedup behavior via collapsed_count.

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?

Front-loaded summary sentence followed by clearly sectioned use cases and field notes; efficient overall, though the parameter bullets partly duplicate the schema and add some length.

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

Completeness4/5

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

Covers routing, auth requirement, output field meanings, dedup semantics, and content provenance; an output schema exists so return-value detail is not strictly required. Nothing essential for correct invocation is missing, though the signal_score discussion overlaps with structured fields.

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 all three parameters; the description's parameter bullets restate defaults and ranges (0-100, default 60, max 10/25) without adding syntax or format detail. Baseline 3 applies.

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 ('Most notable recent news across all tracked stocks: a market-wide briefing') and explicitly contrasts with the sibling get_stock_news ('one symbol'), so an agent can distinguish the two without opening either schema.

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?

Provides three concrete when-to-use scenarios with example queries (morning briefing, catalyst scanning, event monitoring) and explicitly names the alternative tool get_stock_news along with the condition (one symbol) that routes to it.

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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