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goklab

guardvibe

remediation_plan

Generate ordered remediation steps for all six sections after a failed security audit, including secrets, code, dependencies, config, taint, and auth-coverage.

Instructions

Generate a mandatory section-by-section remediation plan from full_audit results. MUST be called after full_audit when verdict is FAIL or WARN. Returns ordered steps for ALL 6 sections (secrets, code, dependencies, config, taint, auth-coverage) with specific tool calls and actions. AI assistants MUST complete every section — skipping sections is not allowed. Example: remediation_plan({path: '.'})

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNoProject root directory.
formatNoOutput format: json for agents (recommended), markdown for humansjson
Behavior4/5

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

With no annotations, the description carries the burden. It reveals the tool returns ordered steps for six specific sections with tool calls and actions, and emphasizes mandatory completion. It does not explicitly state side effects (read-only), but the planning nature implies no destructive actions. This adds context beyond what annotations would provide.

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 sentences plus an example, all front-loaded with the core purpose and key usage rule. Every sentence adds value with no fluff. Highly efficient.

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?

Given no output schema, the description adequately describes the output as ordered steps for all six sections with specific tool calls. It also sets context by linking to full_audit verdicts. Could be more detailed on failure modes or edge cases, but sufficient for an AI to use correctly.

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%, and the description only provides an example usage with path. It adds no new meaning beyond the schema's descriptions for path and format. Baseline score of 3 is appropriate as the description neither enhances nor detracts.

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 generates a mandatory section-by-section remediation plan from full_audit results, specifically after a FAIL or WARN verdict. It lists the six sections and emphasizes completeness, distinguishing it from siblings like full_audit or verify_remediation.

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 states when to use: MUST be called after full_audit when verdict is FAIL or WARN. Also provides a constraint: AI assistants MUST complete every section. This gives clear guidance and exclusions, meeting all criteria.

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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