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fast_context_reader

Extract targeted details from large logs, code files, or cached content by parsing, filtering, or summarizing raw text in about 1-2 seconds, preventing context-window bloat.

Instructions

Parses, filters, or summarizes raw file contents, large logs, cache dumps, or complex schemas using a high-speed worker (DeepSeek-V4 Flash) in ~1-2 seconds. Prevents bloating host agent context window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
focusYesExtraction target (e.g. 'all error stack traces', 'exported interface signatures', 'list of changed state variables').
modelNoOptional model override (default: deepseek-v4-flash).
contentYesThe raw text, code file, log output, or cached content to extract from.
providerNoWorker provider (default: 'deepseek').
Behavior4/5

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 discloses that a high-speed worker (DeepSeek-V4 Flash) is used, gives expected latency (~1-2 seconds), and states the context-bloat prevention effect. It stops short of describing error cases or output format, but for a simple read/filter operation the disclosed behavior is meaningful and non-obvious.

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 with no filler. The first sentence front-loads the action and resource, the second explains the benefit. Every clause earns its place.

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 4-parameter tool with no output schema and no annotations, the description covers the what, the why, and the performance characteristics. It could add example extraction targets or clarify how 'focus' interacts with the parse/filter/summarize modes, but the core calling guidance is present.

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

Parameters3/5

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

Schema description coverage is 100%, so the baseline is 3. The description adds context about the overall purpose and the effect on context window, but it does not provide parameter-specific details beyond what the schema already states for 'content' and 'focus'.

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 specific verbs (parses, filters, summarizes) tied to explicit resources (raw file contents, large logs, cache dumps, complex schemas). It clearly differentiates itself from the sibling consultation/offload tools by positioning itself as a context-preserving extraction utility rather than a deliberation or task-delegation tool.

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 phrase 'Prevents bloating host agent context window' gives a clear usage context: use this when content is large and only a focused extraction is desired. It does not explicitly name alternatives or exclusion conditions, but the sibling names and the description make the intended scenario reasonably clear.

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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