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deprecate_symbol

Record a code symbol replacement to prevent re-emitting outdated signatures. Returns the deprecation status, marking old calls as blocked when superseded.

Instructions

CODING-AGENT REFACTOR RECORD (write, deterministic, no LLM): record that a code symbol old was replaced by new (a function/method/constant renamed or removed in a refactor). This is the fix for the single most common coding-loop memory failure — the model re-emitting a call the refactor already deleted because the old signature is still in its context. A later deprecate_symbol of the same old supersedes the replacement. Then call check_code(generated) before emitting code. Returns the recorded deprecation, and the verdict on the write as remember gives it: a return to a replacement already retired is retired on arrival by the echo guard and comes back blocked: true, with current_id the deprecation that stands.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
newYes
oldYes
reasonNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.20.1

TDQS

A4.3/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden, and it delivers. It discloses that this is a write operation, deterministic, and non-LLM. It explains the supersession rule, the echo guard blocking retired replacements, and the return semantics (`blocked: true`, `current_id`). This goes far beyond what the bare schema provides and gives the agent accurate expectations for side effects and results.

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?

The description is dense but front-loaded with the purpose in the first sentence. Every sentence adds distinct information (behavior, usage, return semantics). It could be more scannable with bullets or paragraphs, but it is not wasteful. The label 'CODING-AGENT REFACTOR RECORD' helps orientation. Slightly long, but each part 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 write tool with no annotations, no output schema, and 0% schema coverage, the description is remarkably complete. It covers the operation's purpose, when to use it, the required follow-up (check_code), and return behavior. The only gaps are lack of `reason` semantics and edge cases like what happens on conflicting replacements. Overall, an agent has enough to invoke it correctly.

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 0%, so the description must compensate. It clearly explains `old` (symbol replaced) and `new` (replacement), but says nothing about the optional `reason` parameter. It also doesn't give types or format hints. It covers the two required params well but leaves one completely undocumented, so it's above baseline but not fully compensating.

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 states a specific verb and resource: 'record that a code symbol `old` was replaced by `new`'. It also grounds it in a concrete scenario (the coding-loop memory failure) which makes the tool's role clear and distinct from the many sibling tools. Though it doesn't explicitly compare to siblings, the purpose is unambiguous and actionable.

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 a clear when-to-use context: it is the fix for a model re-emitting a refactored-away call. It also instructs the caller to invoke check_code(generated) afterward, which is explicit usage guidance. It doesn't mention alternative tools or when not to use it, but the context is strong enough for an agent to select it appropriately.

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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