OpenAI-compatible chat completion through the OpenRouter model gateway (see /api/v1/models for the catalogue). $0.01 charged per call: pay $0.01 exact on Base or Solana, or authorize up to $1.00 with the Base "upto" scheme and still be charged $0.01.
| Name | Required | Description | Default |
|---|---|---|---|
| model | No | Model ID (see /api/v1/models) | deepseek/deepseek-v4-flash |
| stream | No | Enable SSE streaming | |
| messages | Yes | Chat messages array |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / max_tokensRemoved value: -{
- "default": 2000,
- "description": "Defensively capped output tokens",
- "maximum": 2000,
- "type": "integer"
-}Input schema / properties / max_tokensAdded value: +{
+ "default": 2000,
+ "description": "Defensively capped output tokens",
+ "maximum": 2000,
+ "type": "integer"
+}Input schema / properties / max_tokensRemoved value: -{
- "default": 4096,
- "type": "integer"
-}Input schema / properties / messages / itemsAdded value: +{
+ "type": "object"
+}Input schema / properties / model / defaultAdded value: +"deepseek/deepseek-v4-flash"Input schema / properties / streamAdded value: +{
+ "default": false,
+ "description": "Enable SSE streaming",
+ "type": "boolean"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden. It does disclose a meaningful behavioral trait — the $0.01 per-call charge and the payment schemes (Base/Solana exact, or the Base 'upto' authorization) — which is genuinely useful. However, it omits other behavior such as response shape on success/failure and any rate-limits or auth requirements.
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?
Two tight sentences that front-load the purpose before the pricing addendum. No filler, but the pricing detail might have been better as an annotation or a trailing footnote; still, every sentence earns its place.
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?
Given there is no output schema, no annotations, and a called-for service that charges money, the description is adequate but leaves gaps: no guidance on expected input format of the message array, no mention of what the caller receives back, and no note on failures. At three parameters and no annotations, it could do more.
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?
Schema description coverage is 100% and all three parameters (model, stream, messages) are already documented in the schema, so the baseline is 3. The description adds no parameter-level detail beyond the schema, and notably fails to explain what the 'messages' array items should contain.
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?
States a specific action ('OpenAI-compatible chat completion') tied to a clear resource (the OpenRouter model gateway), pointing to the catalogue endpoint for model discovery. None of the sibling tools is another chat-completion tool, so it clearly distinguishes itself in the toolset.
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 contains no guidance on when to use this tool versus alternatives, no context on what kind of requests suit it, and no exclusions. The pricing note is transactional, not usage-directional.
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.
Several tool groups are nearly indistinguishable: wallet_analyze, wallet_spy, and base_wallet_profile all inspect wallets; batch_extract, batch_url_json, and x401_batch_extract all batch-extract URLs; route_task, agentcore_route, and mpp_route all perform routing. An agent would need to read very carefully to avoid selecting the wrong tool.
All names are snake_case, but there is no consistent verb_noun or namespace pattern: many are noun-only (inference, echo, sentiment, server_time), some are prefixed by domain (bazaar_, base_, x402_, rep_), and action prefixes vary widely (fetch_, compile_, extract_, purchase_, route_). The naming is readable but not predictable across the set.
Seventy tools is an extremely large surface for an agent to choose from, and most appear to be independent paid service wrappers. This exceeds the 50+ extreme mismatch threshold in the calibration and creates an overwhelming selection problem.
Relative to its apparent purpose—exposing x402 payments and Bazaar market data—the coverage is extensive: diagnostics, preflight, settlement verification, receipt lookup, wallet checks, Bazaar analytics, web extraction, and text processing are all represented. The main gaps are operational side-effects like creating or updating a Bazaar listing, but those appear to be outside this read/purchase surface.