Compute a repository's Dependency PageRank map and token distribution within a target token budget to identify high-signal context for AI coding agents.
Compute the Dependency PageRank architectural map and token distribution of a repository within a target token budget.
| Name | Required | Description | Default |
|---|---|---|---|
| path | No | Repository root path (default '.') | |
| budget_tokens | No | Target token ceiling (default 32000) |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It never states that this is a read-only computation, whether results are cached or written to disk, or how expensive it is. It does convey the conceptual basis of the output (PageRank over dependencies plus token distribution), which is the only behavioral signal present.
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?
A single front-loaded sentence with no filler. The verb leads, the resource and constraint follow, and every word 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?
There is no output schema, so the description is the only place an agent could learn what the map actually looks like (structure, sections, whether file paths or symbols are returned). It also omits any distinction from ctxray_pack. For a tool with zero annotations and no output schema, this leaves too much unknown.
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 both parameters are already documented. The description's 'target token budget' phrase loosely reinforces budget_tokens but adds no format, range, or interaction detail beyond the schema. Baseline 3 applies.
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 verb ('Compute') and a well-defined resource ('Dependency PageRank architectural map and token distribution of a repository'), which is far more informative than the bare name. It stops short of distinguishing itself from siblings, notably ctxray_pack, which the 'token budget' framing makes it resemble.
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?
There is no when-to-use guidance, no stated prerequisites, and no mention of any alternative tool. The agent must guess whether this is preferred over ctxray_pack or ctxray_skeletonize for repository-level orientation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.