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unpin_memory

Destructive

Permanently remove pinned lines from a memory section by case-insensitive substring match. Use specific text to target only intended lines, as matches are deleted without undo.

Instructions

MUTATING and DESTRUCTIVE: permanently remove pinned lines from a canonical memory section by case-insensitive substring match, with no undo and no restore token. Writes to local disk, machine-wide, so it takes no project_path. A substring can match more lines than intended, so read the section with canonical_memory first and pass text specific enough to hit only what you mean. Fails without changing anything when nothing matches, which makes a dry run safe. Only pinned lines are removable; generated content is rewritten by reconciliation instead. Parameters: section selects which canonical section to modify, one of about, preferences, working-principles, or active-projects; text is the case-insensitive substring, not a whole line and not a pattern, identifying the pinned lines to delete. Returns an object with the section and how many lines were removed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesCase-insensitive substring identifying pinned lines to remove from the selected section.
sectionYesCanonical section to modify. canonical-memory is excluded because it describes the store itself and is regenerated wholesale.
Behavior5/5

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

Beyond the destructiveHint annotation, the description discloses that deletion is permanent with no undo or restore token, writes machine-wide to local disk, takes no project_path, uses case-insensitive matching, and fails without changes when nothing matches. It also explains that only pinned lines are affected, providing rich behavioral context beyond structured hints.

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?

The description opens with a clear MUTATING and DESTRUCTIVE warning, then states the core action, and follows with crucial caveats about matching, failure behavior, scope, parameters, and return value. Every sentence carries important information without redundancy, making it well-structured and appropriately sized.

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?

The description covers the destructive nature, exact matching semantics, failure behavior, scope limitations, and the return object shape. Since there is no output schema, explaining the return format is particularly valuable. Combined with the annotations and input schema, the description fully equips an agent to select and safely invoke the tool.

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?

The input schema already fully documents the parameters, but the description adds essential clarification: text must be a case-insensitive substring, not a whole line and not a pattern. It also enumerates the allowed sections and reiterates the canonical-memory exclusion, supplementing the schema's descriptions.

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 clearly states the tool's function: permanently removing pinned lines from a canonical memory section via case-insensitive substring match. It also distinguishes itself from siblings by noting that only pinned lines are removable and that generated content is handled by reconciliation, making its purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage guidance: read the section with canonical_memory first to avoid unintended matches, warns that a substring can match multiple lines, and clarifies that generated content should not be modified with this tool. It also notes that no-match failures are safe, enabling dry runs, and implicitly contrasts with alternatives by explaining what it cannot do.

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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