Server Quality Checklist

Tool Scores

• chimeraforge_planB
  3.4/5.0
  Behavior3/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose that output includes per-number provenance (measured/extrapolated/estimated/unknown) and that it may report 'why nothing fits,' which are useful behavioral traits. However, it does not describe any side effects, required permissions, or assumptions about how the tool processes inputs (e.g., that it may reach out to hardware databases). It also doesn't clarify whether it performs network access (despite an 'allow_network' parameter). The described behavior is minimal but not misleading, so a 3 is appropriate.

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

  Conciseness5/5

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

  The description is compact and well-structured: it opens with the core purpose, then the provenance detail, then a list of example queries. Each sentence earns its place, and there is no fluff. It is front-loaded with the most important information (what it does and returns). This is exactly how a tool description should be written.

  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?

  This is a complex tool with 27 parameters, no output schema, and no annotations, yet the description is just two sentences. It does not explain the required 'hardware' parameter, the meaning of numeric parameters like 'duty_cycle' or 'safety_target', or how the 'model' parameter interacts with 'model_size'. It also doesn't specify the output format beyond 'candidates with provenance', leaving out details on how the agent should interpret results. The examples give some context, but for an agent to correctly fill all parameters and interpret results, the description is woefully incomplete.

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

  Parameters2/5

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

  Schema description coverage is 0%, meaning the schema provides no parameter documentation. The description mentions the high-level concepts of 'model x quantization x backend x GPU-count' but does not explain any of the 27 parameters, their units, defaults, or relationships. For example, 'hardware' is the only required parameter but its format is unspecified (a GPU name? a type?). 'kv_quant', 'workload', 'lora_rank', and many others are left entirely unexplained. The description fails to compensate for the schema's lack of docs, leaving an agent to guess parameter meanings.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose4/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool's function: recommending a deployment configuration (model, quantization, backend, GPU-count) for a workload, with a fallback to report why nothing fits. It also mentions return of candidates with provenance. This is specific and uses a clear verb+resource pattern. However, it does not explicitly differentiate itself from the sibling tool 'chimeraforge_suggest', which could be seen as overlapping in purpose. The use-case examples ('what GPU do I need', 'will <model> fit') add clarity but do not formally exclude misuse.

  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?

  The description provides explicit usage contexts: 'Use for: ...' with four concrete question patterns. This gives an agent clear conditions for when to invoke this tool. However, it does not mention when NOT to use it or direct it to alternative siblings (e.g., 'compare_api' for comparing specific APIs, or 'suggest' for broader recommendations). The absence of exclusions leaves some ambiguity, but the stated use cases are strong enough for a 4.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• chimeraforge_resolve_modelB
  3.4/5.0
  Behavior2/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure. It says the tool resolves/grounds specs, but it does not disclose read-only behavior, network usage, failure handling, or what happens when a model id cannot be resolved.

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

  Conciseness5/5

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

  The description is one front-loaded sentence with no filler. The parenthetical 'grounds hallucinated specs' adds relevant context without bloating the description.

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

  Completeness3/5

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

  The description is minimally actionable and communicates the core purpose and expected result, but with no output schema and no annotations it leaves important context unexplained, especially around `allow_network` and failure behavior.

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

  Parameters2/5

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

  Schema description coverage is 0%. The description only hints at the `model` parameter via 'model id' and says nothing about the `allow_network` parameter, which is a meaningful gap for an agent deciding how to invoke the tool.

  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 uses a specific verb-resource pair: 'Resolve a model id to real params/architecture' and adds the functional purpose 'grounds hallucinated specs.' This clearly distinguishes the tool from siblings like chimeraforge_plan and chimeraforge_list_hardware.

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

  Usage Guidelines3/5

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

  The context is implied: use this when a model id may be hallucinated and needs to be resolved to concrete architecture/params. However, it does not explicitly state when not to use it or compare it with the alternative sibling tools.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• chimeraforge_list_hardwareA
  3.6/5.0
  Behavior2/5

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

  No annotations are provided, so the description carries the full burden. It does not disclose any behavioral traits such as output format, size limits, or whether it reflects real-time data. The simple listing implies read-only behavior but this is not explicitly stated.

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

  Conciseness5/5

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

  The description is a single, focused sentence that directly states the core action and output characteristics. There is no wasted text, and it is immediately understandable.

  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?

  For a simple, parameterless listing tool with no output schema, the description is adequately complete. It identifies the resource (GPUs) and the key attributes (VRAM/bandwidth/TDP/interconnect). However, it could marginally benefit from a note on data recency or ordering, but this is not critical given the tool's simplicity.

  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?

  The tool has zero parameters, so the baseline score is 4. The description correctly implies no input is needed. Since there are no parameters, no additional semantic information is required.

  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 states the tool's function: 'List known GPUs' with specific attributes (VRAM/bandwidth/TDP/interconnect). This is a specific verb+resource and clearly distinguishes from siblings like chimeraforge_plan and chimeraforge_resolve_model.

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

  Usage Guidelines2/5

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

  There is no guidance on when to use this tool versus alternatives. It does not mention any context, prerequisites, or exclusions. The description is purely functional with no usage direction.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• chimeraforge_suggestA
  3.8/5.0
  Behavior3/5

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

  No annotations exist, so the description carries the behavioral disclosure burden. It communicates core behavior: ranking models against a fit/SLO objective and drawing from three sources: catalog, ollama, and hf. However, it does not disclose external interactions (e.g., reaching out to Ollama or Hugging Face), side effects, failure modes, or whether the operation is read-only.

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

  Conciseness5/5

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

  Two sentences carry the core behavior, user-facing examples, and source list without redundancy. The most important action is front-loaded: 'Rank the models...' instead of burying the intent in filler.

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

  Completeness3/5

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

  The description covers core purpose and high-level sources, which is enough to make a reasonable first call with the one required parameter. However, with 11 parameters, no output schema, no annotation safety clues, and 0% parameter documentation coverage, the description omits too much detail to fully steer an agent through meaningful variations of source, SLO, latency, and quality trade-offs.

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

  Parameters2/5

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

  Schema description coverage is 0%, so the description must compensate, but it only adds meaning to the source concept ('catalog', 'ollama', 'hf') and general context around SLO. The other 10 parameters, including latency_slo_ms, request_rate, quality_target, hf_limit, and budget_usd_month, are left to the agent to infer from their names and defaults, which is risky for a tool with this much configuration surface.

  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 uses a specific verb and object: 'Rank the models that actually fit and hit the SLO on a given GPU.' It clearly identifies itself as the inverse of planning, which separates it from its most likely sibling confusion. The example use cases ('what can I run on a 4090', 'best model for 12GB') make the intent immediately understandable.

  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?

  The description provides concrete usage framing with quoted examples and explicitly contrasts it with planning. It would be stronger if it also stated when not to use it or pointed to the sibling tools, but the 'inverse of planning' hint gives the agent enough context to route appropriately.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• chimeraforge_compare_apiA
  4.2/5.0
  Behavior5/5

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

  With no annotations available, the description carries the full behavioral burden and does it well. It discloses that API prices come from a dated snapshot, that the result reports its age and flags staleness, and instructs the agent not to present old prices as current. This is a meaningful, non-obvious behavioral disclosure.

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

  Conciseness5/5

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

  Three sentences, each earning its place: the first explains what the tool computes, the second gives real user intents, and the third warns about stale pricing. The outcome is well structured and front-loaded.

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

  Completeness3/5

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

  The description is complete on purpose, behavior, and the staleness caveat, but it does not cover the 12-parameter input surface or any expected return format beyond the three high-level outputs. For a tool with no output schema and no annotations, that leaves a meaningful completeness gap.

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

  Parameters2/5

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

  Schema description coverage is 0% and there are 12 parameters, so the description needed to compensate. It only implies concepts like workload and traffic without explaining properties such as hardware, model, duty_cycle, latency_slo_ms, quality_target, or avg_output_tokens. An agent would struggle to set these correctly based solely on this description.

  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 names a specific action (compare), a specific subject (self-hosting vs. hosted APIs), and the three concrete outputs: cheapest feasible GPU fleet sizing, price comparison for identical traffic, and break-even token volume. This clearly differentiates it from siblings like 'plan' and 'suggest'.

  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?

  The description gives explicit, user-quoted use cases: 'is it cheaper to self-host or use the API' and 'when does a GPU pay for itself'. It does not explicitly name alternatives or say when to use a sibling tool instead, so it stops 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.