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list_fixes

Read-onlyIdempotent

Return a remediation plan that removes the most risk with the fewest changes. It prioritizes choke points and shows each fix's risk reduction and route cuts.

Instructions

Return the remediation plan: the fewest changes that remove the most risk, choke points first, each with the share of critical-path risk it eliminates and how many routes it cuts. This is usually the right answer to 'what should we do' - a hundred routes typically collapse into a handful of changes.

Input Schema

NameRequiredDescriptionDefault
appNoRestrict to one application, by a name from get_posture's `applications`: a repository slug or the value of a cloud resource's `app` tag, e.g. 'payments-api'. The match is exact, and a name the environment does not know returns nothing. Omit for the whole environment.

Output Schema

NameRequiredDescriptionDefault
remediationPlanNoThe changes, the one that removes the most risk first.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.38.1
    • changedInput schema / properties / app / description
      Previous value: -"Optional application scope; omit for the whole environment."New value: +"Restrict to one application, by a name from get_posture's `applications`: a repository slug or the value of a cloud resource's `app` tag, e.g. 'payments-api'. The match is exact, and a name the environment does not know returns nothing. Omit for the whole environment."
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "remediationPlan": {
+      "description": "The changes, the one that removes the most risk first.",
+      "items": {
+        "properties": {
+          "coveragePct": {
+            "description": "That sum as a share of the risk on all routes, 0-1.",
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "filename": {
+            "description": "A suggested file name for the fix.",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "kind": {
+            "description": "The form the fix takes, e.g. terraform.",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "pathCount": {
+            "description": "How many routes this change cuts.",
+            "type": [
+              "integer",
+              "null"
+            ]
+          },
+          "rationale": {
+            "description": "Why this change closes the routes it closes.",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "riskCovered": {
+            "description": "The summed score of the routes it cuts.",
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "title": {
+            "description": "What to change, in a line.",
+            "type": [
+              "string",
+              "null"
+            ]
+          }
+        },
+        "type": [
+          "object",
+          "null"
+        ]
+      },
+      "type": [
+        "array",
+        "null"
+      ]
+    }
+  },
+  "type": "object"
+}
  2. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is covered. The description adds value beyond them by disclosing output semantics — ranked choke points, per-item risk share and route cuts — which tells the agent what 'fixes' actually contains. It stops short of noting result size or whether the plan is exhaustive versus truncated.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the core verb and resource before the explanatory framing. The closing 'a hundred routes typically collapse into a handful of changes' is helpful intuition but is the least load-bearing sentence and pushes toward verbosity.

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?

An output schema exists, so return values need not be explained, and annotations cover the safety profile. The description still supplies the interpretive layer — what ranking means and what each fix reports — leaving only the simulate_fix relationship uncovered. Adequate and nearly complete for a one-parameter read tool.

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?

Only one parameter with 100% schema description coverage, including exact-match semantics and the 'omit for whole environment' default, so the schema carries this fully. The description contributes nothing about the `app` filter, which is acceptable at this coverage level but adds no marginal meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Return the remediation plan') and adds real scope detail: fewest changes that remove the most risk, choke points first, with two named output metrics (share of critical-path risk eliminated, routes cut). It distinguishes itself from list_attack_paths/enumerate tools by output shape, though it never names simulate_fix, the sibling it most needs to be separated from.

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?

Explicitly frames when to reach for it: 'usually the right answer to what should we do'. That is genuine usage context. What is missing is any exclusion or alternative routing — notably no mention of when to prefer simulate_fix to test a candidate change instead of reading the plan.

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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