slimtoken.high_context_presets

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

With no annotations, the description carries the full burden and does a good job: it discloses the computation assumptions (config_optimizer, q4_0 KV, flash attn, full offload) and provides the formula for effective raw-token capacity. It also clarifies that rows represent presets and that best=true filters to the largest. Minor omissions include not stating default behavior when vram_gb is omitted.

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 four sentences, front-loaded with the primary purpose, then details the computation, the formula, and a useful parameter tip. Every sentence adds value and there is no redundancy or filler.

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 the moderate complexity (VRAM tiers, compression, formulas), the description provides sufficient context for an agent to understand what the tool returns and how the values are computed. The lack of an output schema is partially mitigated by the description's mention of 'rows' and the formula. The main gap is not specifying the full return set when vram_gb is omitted.

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 coverage is 100%, so the baseline is 3. The description adds no new parameter-specific syntax beyond the schema, but it does provide context for interpreting the output (formula for effective capacity). This is helpful but not essential, given the schema already explains both parameters clearly.

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 identifies the tool as providing high-context VRAM-tier configs for both dense and MoE models, with a specific scope of showing how compression expands context. It distinguishes itself from siblings like list_model_presets by focusing on VRAM tiers and effective context capacity. However, it lacks an explicit verb like 'list' or 'get', which slightly reduces clarity.

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 gives a specific usage hint for the 'best' parameter ('Use best=true...'), which is helpful. However, it does not explicitly state when to use this tool over alternatives like list_model_presets or get_config. The context is implied by the title and description, but no exclusions or alternative comparisons are provided.

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