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brnbio
by brnbio

plan

Generate development tickets by analyzing gaps, required changes, and dependencies from project context, exporting a JSON draft with estimates, labels, and technical checklists.

Instructions

Erstellt Tickets basierend auf dem project_context.

Analysiert:

  • Gap zwischen IST und SOLL

  • Benötigte Änderungen an DB, Backend, Frontend

  • Dependencies zwischen Tasks

Generiert Tickets mit:

  • 4h oder 8h Schätzung

  • Labels (Backend, Frontend, Testing, Database)

  • Technische Checkliste

  • Betroffene Dateien/Pfade

Output: tickets_draft.json

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
clarificationsNoAntworten auf Rückfragen aus dem vorherigen Durchlauf
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses key behavioral aspects: it analyzes IST/SOLL gap, DB/backend/frontend changes, dependencies, generates tickets with estimates, labels, checklists, and affected files, and outputs to tickets_draft.json. This provides solid insight into what happens when invoked, though it does not mention side effects like file writing explicitly.

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 well-structured and front-loaded with the primary action. Bullet points efficiently list analysis areas and ticket attributes. Every line contributes meaningful information without unnecessary filler.

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 tool with moderate complexity and no output schema, the description covers the input source (project_context), the analysis steps, the output format (tickets_draft.json), and the optional clarifications parameter. It omits details about error handling or edge cases, but the provided information is sufficient for an agent to understand the tool's role and expected outcome.

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 single parameter 'clarifications' is fully described in the schema as 'Antworten auf Rückfragen aus dem vorherigen Durchlauf' (answers to follow-up questions from the previous run). Schema coverage is 100%, so the description adds no additional semantic value beyond what the schema already provides, matching the baseline of 3.

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 verb and resource: 'Erstellt Tickets basierend auf dem project_context' (creates tickets based on the project context). It also distinguishes itself from siblings 'inspect' and 'export' by focusing on ticket generation, not inspection or export.

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

Usage Guidelines3/5

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

The description implies usage context by describing analysis of gaps, changes, and dependencies, but it does not explicitly state when to use this tool versus alternatives. No when-not conditions or alternative tool references are provided.

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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