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delimit_sense

Inspect, cluster, and promote sensed signals from the signal corpus into ledger items. Also query, digest, show, freeze, or check status.

Instructions

Review and manage the signal corpus (LED-877).

When to use: to inspect, cluster, or explicitly promote sensed signals into ledger items. Signals live separately from the ledger so noise doesn't pollute it. When NOT to use: to fetch new signals (use the platform-specific sensors like delimit_reddit_scan / delimit_github_scan) or write ledger items directly (delimit_ledger_add).

Sibling contrast: platform sensors capture; this manages the captured corpus and bridges it into the ledger.

Side effects: "promote" writes a new ledger item (via the ledger manager). "freeze" cold-archives a month of signals. "query", "digest", "show", "status" are read-only against ~/.delimit/intel/signals/.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionNoOne of "query" (default), "digest", "show", "promote", "freeze", "status".query
since_daysNoLookback window in days (query/digest). Default 1.
platformNoFilter source platform — "reddit", "x", "github", "hn". Empty = all.
limitNoMax rows for query. Default 50.
signal_idNoSIG-XXXX id for "show" / "promote".
ledgerNoTarget ledger for promote — "ops" (default) or "strategy".ops
priorityNoPriority for promoted item — "P0", "P1", "P2".P2
monthNoYYYY-MM string for "freeze".

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations, the description fully discloses behavioral traits: side effects for each action (e.g., 'promote' writes a new ledger item, 'freeze' cold-archives) and the storage location (~/.delimit/intel/signals/). Read-only and write actions are clearly separated.

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 is concise and well-structured with clear sections: when to use, not to use, sibling contrast, and side effects. It is front-loaded with the main purpose and avoids unnecessary detail.

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?

Given the presence of an output schema (noted in context signals), the description need not explain return values. It covers all essential aspects: purpose, usage, side effects, and sibling distinction, making it complete for an agent.

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 coverage is 100%, so the baseline is 3. The description adds context for the 'action' parameter by explaining each action's effect, but other parameters are already well-documented in the schema. No significant additional meaning beyond schema.

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 purpose: 'Review and manage the signal corpus (LED-877).' It specifies actions like inspect, cluster, and promote, and distinguishes from sibling tools like delimit_reddit_scan and delimit_github_scan.

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?

Explicitly provides 'When to use' and 'When NOT to use' sections, detailing appropriate use cases (inspect, cluster, promote) and exclusions (fetch new signals, write ledger items directly). Also includes sibling contrast for additional guidance.

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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