get_manipulation[FORENSICS] Manipulation-risk analysis for one asset: composite manipulation score, coordinated-pump probability, fake-engagement risk, liquidation-cascade detection. Richer than the per-signal manipulation_score field — this is the full standalone read. Mirrors REST /manipulation/{coin}. Analytical, not advice.
| Name | Required | Description | Default |
|---|---|---|---|
| coin | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, so the read-only nature is already conveyed. The description adds behavioral context by stating 'Analytical, not advice' and 'Mirrors REST /manipulation/{coin}', which inform expectations about output nature and API alignment. It does not introduce any contradiction with the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, each carrying meaningful information: a forensics tag and component list, a differentiation from per-signal data, and an API mirror plus a 'not advice' caveat. It is front-loaded with the core purpose and wastes no words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with no output schema, the description is robust: it lists the analysis components, clarifies the scope ('one asset'), notes the REST mirror, and includes a disclaimer. It does not describe the output structure or error conditions, but given the relative simplicity and existing annotations, it is sufficiently complete for an agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one required 'coin' parameter with no description (0% coverage). The description compensates somewhat by stating 'for one asset,' indicating that 'coin' identifies the asset, but it lacks explicit format details (e.g., symbol vs. name) and does not explain the parameter further. Given the low schema coverage, more detail would be helpful, placing this at a baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs 'manipulation-risk analysis for one asset' and enumerates the specific outputs (composite score, coordinated-pump probability, fake-engagement risk, liquidation-cascade detection). It explicitly differentiates from the per-signal manipulation_score field, positioning this as the full standalone read, which distinguishes it from sibling tools like get_signal.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description says 'Richer than the per-signal manipulation_score field — this is the full standalone read,' which provides guidance on when to use this tool versus relying on the per-signal field. It also notes the single-asset scope and the REST mirror, giving context for API users. However, it doesn't explicitly mention alternative tools or when not to use it, so it falls slightly short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clearly distinct purposes with detailed descriptions, but there are clusters of similar concepts (e.g., get_liquidity_map vs get_liquidation_map, get_state vs get_state_brief, multiple signal-related tools) that could cause misselection despite thorough documentation.
All tools follow a consistent lowercase verb_noun pattern, predominantly get_* nouns, with only a few non-get verbs like list_signals, rank_trades, log_trade, etc., but the style is uniform.
With 52 tools, the surface is extremely heavy for an agent to navigate. While the server's scope is broad, the count far exceeds the typical 3-15 range and falls into the 'too many' category.
The tool set covers the full lifecycle for journaling, signals, market analysis, and proof, with no major dead ends. Minor gaps exist, such as no dedicated get_trade_by_id (workaround via get_journal) and no get_market_state tool despite being referenced in get_state.