Fixter

set_issue_digest_config

Create or update the authenticated customer's issue-surfacing digest config. ADMIN only. Only the fields you provide are changed; any field you omit keeps its current value. If mode is provided it must be one of OFF, INTERNAL, LIVE. When no config exists yet for the customer, omitted fields fall back to sensible defaults. Returns the saved config as JSON.

Input Schema

TableJSON Schema

Name	Required	Description
`mode`	No	Digest mode: OFF, INTERNAL, or LIVE. Omit to keep the current mode.
`lookbackDays`	No	Number of days to look back when generating the digest. Omit to keep the current value.
`scheduleCron`	No	Cron expression for the digest schedule. Omit to keep the current value.
`splitMessages`	No	Post each surfaced issue as its own Slack message instead of one combined digest (for message-based integrations like Linear's Slack bot). Omit to keep the current value.
`scheduleTimezone`	No	Timezone for the schedule (e.g. UTC). Omit to keep the current value.
`deliveryChannelId`	No	Slack channel id to deliver the digest to. Omit to keep the current value.

TDQS

A4.7/5.0

Behavior5/5

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

With no annotations, the description carries the full burden and delivers: partial update semantics (omitted fields keep current value), validation (mode must be OFF/INTERNAL/LIVE), default behavior for non-existent configs, access requirement (ADMIN only), and return value (saved config as JSON). This is exemplary transparency for a mutation tool.

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?

Four sentences, front-loaded with purpose and then behavioral details. Every sentence conveys necessary information with no redundancies or fluff. Perfectly sized for the tool's complexity.

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?

The description covers all critical aspects: purpose, admin restriction, partial update behavior, mode validation, defaults for missing config, and return format. No gaps remain given the moderate complexity, no annotations, and no output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds value by explaining the general partial-update contract and mode validation, which gives semantic context beyond individual parameter descriptions. It doesn't enumerate each parameter, but the schema already does.

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 verb+resource: 'Create or update the authenticated customer's issue-surfacing digest config.' It distinguishes itself from sibling read tools like get_issue_digest_config and other set_* tools by specifying exactly what it modifies.

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?

The description gives clear context for when to use the tool (to create or update a digest config) and includes an important prerequisite ('ADMIN only'). It doesn't explicitly name alternatives (e.g., 'use get_issue_digest_config to read'), but the create/update purpose is self-evident and distinct from siblings.

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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TDQS

A3.8/5.0

Disambiguation2/5

Several tool pairs are near-duplicates, including three deprecated aliases (add_investigation_alert_channel vs add_alert_channel, list_investigation_alert_channels vs list_alert_channels, remove_investigation_alert_channel vs remove_alert_channel) that muddy the surface. Additionally, suppress_signal and create_ignore_rule both suppress alerting via different mechanisms, which could cause misselection despite detailed descriptions.

Naming Consistency4/5

The vast majority of tools follow a clear verb_noun snake_case pattern (create_api_test, list_issues, set_alert_rule_status). A few bare-noun tools (logs, spans, metrics) and the standalone verb correlate break the pattern slightly, but overall the naming is highly consistent and predictable.

Tool Count1/5

With 52 tools, this is on the extreme end of the calibration scale. Even accounting for the broad scope of an observability platform, the count is excessive and includes several deprecated redundancies that inflate it further.

Completeness5/5

The toolset provides comprehensive CRUD/lifecycle coverage across all major domains: alert rules (create, read, update, delete, status, delivery, preview), API tests (create, read, update, delete, run history, credentials), ignore rules and suppressions, issues with digest config, investigations with claim/read, channels, credentials, and rich query tools (logs, spans, metrics, SQL, traces, correlation). No obvious dead ends or missing core operations.

Resources

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