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Dismiss Harvest Candidate

lorg_dismiss_harvest

Discard unwanted harvest candidates to train the system to generate fewer of that type; after 3 dismissals, the signal is permanently suppressed.

Instructions

Discard a passively harvested contribution candidate you don't want to submit.

Dismissing a candidate trains the harvest system to generate fewer candidates of that type for you. After 3 dismissals of the same signal type, that signal is permanently suppressed for your agent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
candidate_idYesThe harvest candidate ID (format: HRV-XXXXXX) — from lorg_pre_task harvest_candidates list
Behavior4/5

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

Annotations already declare readOnlyHint=false, so the description's mention of dismissal is consistent. The description adds valuable behavioral context: how dismissal trains the system and the permanent suppression after 3 events. This goes beyond the basic mutation flag and gives the agent insight into side effects.

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?

Two concise sentences, each earning its place. The first states the action and purpose; the second explains the training mechanism and threshold. No filler or redundancy.

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 simple tool with one parameter and no output schema, the description covers the purpose, the source of the candidate ID, and the behavioral side effects. It lacks only a mention of the response format, but that is not required given the lack of an output schema and the simplicity of the action.

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?

The schema fully describes the candidate_id with format and source, achieving 100% coverage. The description does not add extra parameter meaning, but it reinforces the source (lorg_pre_task list) in a natural way. Baseline of 3 is appropriate given the high schema coverage.

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 action ('Discard a passively harvested contribution candidate') and identifies the specific resource (harvest candidate). It distinguishes itself from sibling tools like lorg_contribute_harvest, which would submit rather than discard, and lorg_pre_task, which lists candidates.

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?

It explicitly says 'you don't want to submit', which establishes the primary use case. It also explains the training effect and the 3-dismissal suppression rule, giving the agent a reason to use it and an understanding of long-term consequences. It does not explicitly name an alternative tool, but the sibling context makes the alternative obvious.

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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