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log-10x

Log10x MCP Server

Official

Explain enforcement mode

log10x_explain_mode
Read-onlyIdempotent

Explains a chosen log enforcement mode in service-level plain language, with cost math and apply or preview next steps.

Instructions

CALL THIS AFTER log10x_cost_options when the user picks a mode. Explains the chosen enforcement mode (drop / sample / compact / tier_down / offload / observe_only) in service-level plain language, with dollar math when byte metrics are available. Returns must_render_verbatim (plain-text three-section card, no markdown), must_ask_user (Apply or Preview choice), and forbidden_next_actions (locks apply tools and log10x_preview_filter until the user picks). routes_to.apply routes all non-observe modes to log10x_configure_engine; observe_only has routes_to.apply === null (no enforcement step). routes_to.preview routes to log10x_preview_filter with { service, mode }.

Input Schema

NameRequiredDescriptionDefault
modeYesWhich enforcement mode to explain. Keep-everything levers come first, then the lossy opt-ins. `compact` = keeps everything: engine minifies events; all events still reach the stack, and the destination's expander rebuilds them (how exactly, and which searches see the full text, is per destination). `offload` = keeps everything: engine diverts matched events to a customer-owned S3 bucket; readable via log10x_retriever_query. `tier_down` = keeps everything: engine stamps the routeState marker; a routing rule moves those events to a cheaper tier in the same destination (Datadog Flex / CloudWatch IA / Azure Monitor Basic or Auxiliary Logs). `sample` = lossy opt-in: engine passes 1-in-N events through to the stack; the rest are discarded. `drop` = lossy opt-in: engine hard-drops matched patterns at the Receiver before delivery. `observe_only` = engine observes and fingerprints but does not act; use to baseline volume before committing.
serviceYesService name to personalize the explanation with service-level volume and cost figures.
destinationNoAuto-detected destination stack or forwarder. When omitted the tool infers from envs.json / env vars. Used to name the specific vendor in the explanation ("your Datadog workspace", "your Splunk index", etc.).
effective_ingest_per_gbNoCustomer-supplied $/GB rate used for the dollar overlay. When set, source_disclosure.rate_source='customer_supplied'. When absent, the shared rate resolver falls back to envs.json analyzerCost → LOG10X_ANALYZER_COST → the destination default rate (a list price where the vendor sells logs per GB) → unset (no dollar overlay).

Output Schema

NameRequiredDescriptionDefault
dataNo
toolYes
viewNosummary
imagesNo
actionsNo
summaryYes
warningsNo
truncatedNo
next_cursorNo
render_hintNo
generated_atYes
schema_epochYes
schema_versionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.30.8
    • changedInput schema / properties / effective_ingest_per_gb / description
      Previous value: -"Customer-supplied $/GB rate used for the dollar overlay. When set, source_disclosure.rate_source='customer_supplied'. When absent, the shared rate resolver falls back to envs.json analyzerCost → LOG10X_ANALYZER_COST → destination list price → unset (no dollar overlay)."New value: +"Customer-supplied $/GB rate used for the dollar overlay. When set, source_disclosure.rate_source='customer_supplied'. When absent, the shared rate resolver falls back to envs.json analyzerCost → LOG10X_ANALYZER_COST → the destination default rate (a list price where the vendor sells logs per GB) → unset (no dollar overlay)."
    • changedInput schema / properties / mode / description
      Previous value: -"Which enforcement mode to explain. Keep-everything levers come first, then the lossy opt-ins. `compact` = keeps everything: engine minifies events ~50-80% losslessly; all events still reach the stack. `offload` = keeps everything: engine diverts matched events to a customer-owned S3 bucket; readable via log10x_retriever_query. `tier_down` = keeps everything: engine stamps the routeState marker; a routing rule moves those events to a cheaper storage tier (Datadog Flex / CloudWatch IA / Azure Monitor Basic or Auxiliary Logs). `sample` = lossy opt-in: engine passes 1-in-N events through to the stack; the rest are discarded. `drop` = lossy opt-in: engine hard-drops matched patterns at the Receiver before delivery. `observe_only` = engine observes and fingerprints but does not act; use to baseline volume before committing."New value: +"Which enforcement mode to explain. Keep-everything levers come first, then the lossy opt-ins. `compact` = keeps everything: engine minifies events; all events still reach the stack, and the destination's expander rebuilds them (how exactly, and which searches see the full text, is per destination). `offload` = keeps everything: engine diverts matched events to a customer-owned S3 bucket; readable via log10x_retriever_query. `tier_down` = keeps everything: engine stamps the routeState marker; a routing rule moves those events to a cheaper tier in the same destination (Datadog Flex / CloudWatch IA / Azure Monitor Basic or Auxiliary Logs). `sample` = lossy opt-in: engine passes 1-in-N events through to the stack; the rest are discarded. `drop` = lossy opt-in: engine hard-drops matched patterns at the Receiver before delivery. `observe_only` = engine observes and fingerprints but does not act; use to baseline volume before committing."
  2. First observedv1.30.7

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint, but the description adds real behavioral context: must_render_verbatim (plain text, no markdown), must_ask_user, and forbidden_next_actions that lock apply tools and log10x_preview_filter until the user picks. This is unusually rich disclosure, though much of it describes return fields that the output schema may already carry.

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?

Front-loaded with the ordering precondition and information-dense throughout. However, the extended enumeration of return fields (must_render_verbatim, must_ask_user, forbidden_next_actions, routes_to.*) partially duplicates what the output schema should convey, adding some bulk.

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?

With annotations, a full output schema, and 100% param coverage already present, the description supplies exactly the missing orchestration layer: when to call it, what it returns semantically, and where it routes. Nothing needed to invoke it correctly appears to be 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% and the mode enum documents each lever in depth, so the schema does the heavy lifting. The description restates the mode list but adds no syntax or format meaning beyond what the schema provides, so the baseline of 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?

States a specific verb and resource (explain a chosen enforcement mode) and enumerates the exact modes covered. It clearly differentiates itself from siblings by naming log10x_cost_options as its predecessor and log10x_configure_engine / log10x_preview_filter as downstream routes.

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?

Explicit trigger ('CALL THIS AFTER log10x_cost_options when the user picks a mode'), plus routing rules that tell the agent which sibling to invoke next for each mode. The observe_only null-routes case is called out, removing the main ambiguity.

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