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important_symbols

Rank code symbols by their dependency load using weighted PageRank. Automatically seeds from your current git diff to show what your edits most depend on, helping avoid breaking critical parts.

Instructions

Rank the most load-bearing symbols by weighted PageRank over the call/type/import edge graph — what the rest of the code most depends on. Run before editing to see the spine you shouldn't reinvent or break. By DEFAULT (no personalize) it auto-seeds from your current git diff, returning importance relative to your current changes; pass personalize (names, refs, or sym_<hex> handles you're working on) to seed it explicitly, or a single "global" to force whole-repo PageRank. The result is a labeled object: mode (which scale), seed_source (seed provenance), and symbols.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax load-bearing symbols to return.
personalizeNoSymbols to bias importance toward (the symbols you're editing/querying) — names, refs (`path::name`), or `sym_<hex>` handles; the random surfer teleports back to these, lifting the spine *they* depend on. A `sym_<hex>` handle resolves to its logical symbol's members; otherwise the entry is resolved by ref then name (ambiguous/missing entries are skipped, never fatal). LEAVE EMPTY to auto-seed from your current git diff (the default — "importance relative to your current changes"). Pass a single `"global"` to force whole-repo PageRank instead.
Behavior4/5

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

No annotations provided, so description carries full burden. Discloses that it uses PageRank, auto-seeds from git diff, and returns a labeled object. Explains the effect of personalize parameter. Could mention if it is read-only or has side effects, but overall good transparency.

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

Conciseness4/5

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

Description is moderately concise and front-loads the main purpose. Slightly verbose but every sentence adds value. Could be structured with bullet points, but still effective.

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

Completeness5/5

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

For a tool with 2 parameters, no output schema, and no annotations, the description covers the tool's behavior, return value, and usage scenarios completely. No gaps identified.

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?

Schema coverage is 100%, but description adds significant meaning: explains default behavior for personalize, how auto-seeding works, and the effect of global. Adds value beyond the schema alone.

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?

Clearly states that it ranks the most load-bearing symbols by weighted PageRank over the call/type/import edge graph. Distinguishes from sibling tools like memory_search, semantic_search, etc., which have different purposes.

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?

Explicitly says 'Run before editing to see the spine you shouldn't reinvent or break.' Explains default behavior and how to customize with personalize parameter. Does not explicitly state when not to use, but the context is 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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