Tachyo

marketsummary__find_longs

[marketsummary] Long candidates — MEAN-REVERSION: oversold / beaten-down names that have NOT bounced yet (down over the week, lagging BTC, still basing today), survival-gated by volume so the list is not death-spirals. This is our one edge read long-side; public catalysts/listings are NOT here because they are priced in (the move happens pre-announcement). Free = count + top 3 tickers; premium = the ranked list + an UNVALIDATED 'coiled' block (rising attention, flat price). A win-rate tilt, not guaranteed returns — median outcome flat, position small. Not financial advice.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`payment`	No
`window_days`	No
`session_token`	No

TDQS

A3.5/5.0

Behavior4/5

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

Discloses key traits: survival-gated by volume, win-rate tilt, median outcome flat, and not financial advice. With no annotations, description carries full burden and does so well.

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

Conciseness3/5

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

Single paragraph, information-dense but lacks clear structure. Some padding (e.g., premium vs free explanation) could be streamlined, but not overly verbose.

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

Completeness2/5

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

No output schema and 0% parameter coverage. Description covers domain logic but omits input/output specifics. Users cannot infer how to set parameters or parse results.

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

Parameters1/5

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

Schema coverage is 0%, but description provides zero information about the three parameters (payment, window_days, session_token). This is a critical failure for tool usage.

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 clearly defines the tool's purpose: finding long candidates based on mean-reversion, specifically oversold names that haven't bounced. It distinguishes itself from catalyst-based tools and sets clear scope.

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?

Provides context on when to use (mean-reversion) and when not (catalyst-based longs). Mentions premium vs free tiers but doesn't explicitly name sibling tools for comparison.

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

A3.8/5.0

Disambiguation5/5

Each tool targets a distinct aspect of market analysis or token safety, with clear descriptions that avoid overlap. Tools like find_longs and find_shorts are opposites, and other get_* tools each address unique metrics (e.g., buzz, attention shifts, smart money flow). No two tools have ambiguous boundaries.

Naming Consistency4/5

Tools are prefixed by category (marketsummary__, tokensafety__, verify__), and most use a verb_noun pattern (e.g., get_liquidity, find_longs). However, there is some variation: 'ask_market', 'track_narrative', and longer names like 'attention_vs_price_divergence' break the pure 'get_' pattern. Overall, the naming is logical and predictable.

Tool Count5/5

With 24 tools, the server covers a wide range of crypto market analysis, from general summaries to specific signals (e.g., conviction gap, smart money flow) and token safety. The count is well-scoped for the domain; each tool serves a clear purpose without being excessive.

Completeness5/5

The tool set is comprehensive for a market analysis server: it includes natural language querying, trend detection, sentiment, liquidity, whale activity, safety checks, and wallet verification for premium access. Missing trading actions are outside the stated purpose, so no gaps are apparent.

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