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Glama

decode_error

Decode exit codes, Kubernetes pod statuses, HTTP gateway errors, and common Docker/ECS/AWS/Terraform/TLS/DNS messages to get meanings, likely causes, diagnostics, and fixes.

Instructions

Decode an exit code, Kubernetes pod status, HTTP gateway error, or common Docker/ECS/AWS/Terraform/TLS/DNS error message (e.g. "137", "CrashLoopBackOff", "502", "Error acquiring the state lock"). Returns what it means, likely causes, diagnostic commands, fixes, and related incident scenarios. Offline and read-only.

Input Schema

NameRequiredDescriptionDefault
errorYesThe exit code, status, or error text (e.g. "137", "exit code 143", "OOMKilled", "502 Bad Gateway", "exec format error")
platformNoOptional hint to rank matches: "kubernetes", "docker", "ecs", "aws", "terraform", "linux", "http", "network", or "tls"

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: 'Offline and read-only' rules out side effects or auth requirements, and it enumerates the return payload (meaning, causes, diagnostic commands, fixes, related scenarios). It does not say what happens on an ambiguous or unmatched error, which is the main residual gap.

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?

Three tight sentences: input scope first, return contents second, safety profile last. No filler, and the most decision-relevant information (what it decodes) is front-loaded.

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?

There is no output schema and no annotations, so the description must supply both the return shape and the safety posture — it does exactly that. For a two-parameter offline lookup tool, nothing an agent needs in order to call it correctly is missing.

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% — both 'error' and 'platform' are fully documented in the schema, including accepted platform values and example inputs. The description's input examples largely repeat what the schema already says, so it adds no new parameter semantics beyond the baseline.

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?

A specific verb ('Decode') applied to an explicitly enumerated set of resources — exit codes, k8s pod statuses, HTTP gateway errors, and Docker/ECS/AWS/Terraform/TLS/DNS messages — with concrete input examples. The scope is unmistakably different from siblings like search_incident_scenarios or get_scenario_runbook, though the description never names an alternative.

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?

Usage is implied by the accepted input types and the 'platform' ranking hint, but there is no explicit when-to-use/when-not statement and no routing to sibling tools (e.g. get_scenario_runbook) for questions this tool cannot answer. An agent can infer the fit, but nothing is spelled out.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.