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search_issues

Search Jira issues with JQL to find security incidents, open vulnerabilities, and track remediation tasks. Returns key details like status, priority, assignee, and labels.

Instructions

Search Jira issues using JQL (Jira Query Language). Returns key, summary, status, type, priority, assignee, reporter, created/updated dates and labels. Use for finding security incidents, open vulnerabilities, or tracking remediation tasks. Examples: project = SEC AND status != Done, assignee = currentUser() AND priority = High, labels = security-incident ORDER BY created DESC.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jqlYesJQL query string. Examples: "project=SEC AND status=Open", "priority=Critical AND labels=security-incident ORDER BY created DESC"
fieldsNoSpecific fields to return. Default: summary,status,issuetype,priority,assignee,reporter,created,updated,labels. Add "description" for full text.
start_atNoPagination offset (default: 0). Use with max_results to paginate large result sets.
max_tokensNoMax output tokens. Default: 20000.
max_resultsNoMaximum issues to return (default: 50, max: 100). Reduce if token limit hit.
break_token_ruleNoBypass token limit check.
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses the return fields, demonstrates query syntax, and implies a list result. However, it does not mention default ordering, pagination behavior, or error handling, which are minor gaps for a search tool.

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 efficient and well-structured: first sentence states the function, second lists return fields, third provides domain-specific use cases, and the remaining sentences give concrete examples. No wasted words.

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 moderate complexity (6 params, no output schema), the description covers purpose, return fields, and use cases, while the schema handles parameter details. It is complete enough for an agent to select and invoke the tool correctly without additional context.

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 100%, so the schema already documents all parameters. The description adds value via JQL examples but does not elaborate on parameter semantics beyond what the schema provides. Baseline 3 is appropriate.

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 'Search Jira issues using JQL' with a specific verb and resource, and the JQL method distinguishes it from get_issue and other issue tools. It also lists the exact fields returned, making the 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 Guidelines4/5

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

It provides clear use cases ('Use for finding security incidents, open vulnerabilities, or tracking remediation tasks') and includes example queries that show the intended usage. It does not explicitly contrast with sibling tools like get_issue, but the context is sufficient for an agent to decide when to use this search tool.

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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