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hybrid-cloud-outboxes

Guide for creating and maintaining outbox-based eventually consistent operations in Sentry. Most commonly used for cross-silo data replication, but applicable anywhere eventual consistency is needed — including single-silo deferred side effects, audit logging, and event fanout. Use when asked to "add outbox", "add outbox replication", "replicate model to control silo", "replicate model to cell", "add outbox category", "write outbox signal receiver", "debug stuck outboxes", "outbox not processing", "data not replicating", "test outbox", "migrate model to use outboxes", "backfill outbox data", "outbox coalescing", "ReplicatedCellModel", "ReplicatedControlModel", "OutboxCategory", "OutboxScope", or "outbox_runner". Covers model mixins, category registration, signal receivers, testing, backfill, and debugging workflows.

77

Quality

97%

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SKILL.md
Quality
Evals
Security

Quality

Content

92%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

An excellent body: a routing table, complete model templates, executable test patterns, a diagnostic table, and a final verification checklist, with details correctly pushed to one-level-deep reference files. The only weakness is mild redundancy in section lead-ins and test examples, which costs a single point on conciseness.

Suggestions

Drop lead-in sentences that restate the 2.1 table (e.g. 'Use this when a Cell model needs to replicate data to the Control silo') — the table already communicates the mixin choice.

Trim the 7.2 test examples to one fully-worked pattern plus one-line statements of what the remaining tests should assert, moving the rest to the referenced hybrid-cloud-test-gen material.

DimensionReasoningScore

Conciseness

The body is dense and technical — blockquote constraints, a routing table, code-heavy steps — and assumes Claude's competence (no explanation of transactions, signals, or general Django concepts). Section lead-ins occasionally restate what the 2.1 table already conveys, and the test section carries four full example functions where the pattern is established after two. Not 5: minor trimming is possible; not 3: there is no padding of concepts Claude already knows.

4 / 5

Actionability

Copy-paste-ready model templates with imports and manager wiring, executable test code using real utilities ('outbox_runner', 'outbox_context(flush=False)', 'assume_test_silo_mode_of'), and a debug table citing specific metrics ('outbox.coalesced_net_processing_time') and Celery tasks. Not 4: the only placeholders (e.g. 'my_mapping_service') are intentional template substitution points, not missing steps.

5 / 5

Workflow Clarity

Step 1's intent-routing table dispatches to a sequenced Steps 2–8, a symptom→cause→investigation table provides an error-recovery loop, and Step 9 is an explicit pre-flight checklist that validates the batch/backfill operations. Not 4: validation checkpoints are explicit, not implicit; not capped at 3 because the checklist covers the destructive/batch cases.

5 / 5

Progressive Disclosure

The body is an overview plus core templates; detail is split into four real reference files (all verified to exist and be substantive), each clearly signaled with 'Load references/... for...' and exactly one level deep — the single cross-link in debugging.md points to a sibling top-level file also directly reachable from SKILL.md. Not 4: the split is appropriate and navigation is trivial.

5 / 5

Total

19

/

20

Passed

Description

100%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A model description: concrete capabilities, an explicit 'Use when' clause with abundant natural trigger phrasings, comprehensive scope coverage, and a highly distinctive Sentry-specific niche. All four dimensions sit firmly at the top anchor.

DimensionReasoningScore

Specificity

The description names multiple concrete capabilities — 'creating and maintaining outbox-based eventually consistent operations', 'model mixins, category registration, signal receivers, testing, backfill, and debugging' — comprehensively covering the skill's scope. Not 4: no coverage gaps relative to the skill's actual sections; every action is concrete rather than generic.

5 / 5

Completeness

Explicitly answers both 'what' ('Guide for creating and maintaining outbox-based eventually consistent operations in Sentry... Covers model mixins, category registration, signal receivers, testing, backfill, and debugging workflows') and 'when' ('Use when asked to...' followed by concrete trigger phrases). Not 4: neither half is missing or weakly implied.

5 / 5

Trigger Term Quality

Extensive natural trigger phrasing — 'add outbox', 'outbox not processing', 'data not replicating', 'backfill outbox data', 'test outbox', 'debug stuck outboxes', 'outbox coalescing' — alongside synonyms and API identifiers like 'outbox_runner', 'ReplicatedCellModel', and 'OutboxCategory'. Not 4: common user phrasings and their variations are all present.

5 / 5

Distinctiveness Conflict Risk

A clear niche — Sentry's hybrid-cloud outbox pattern — with distinct triggers ('CellOutbox', 'OutboxScope', 'replicate model to control silo') that no other plausible skill would claim. Not 4: no meaningful overlap risk with closely related skills.

5 / 5

Total

20

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

getsentry/sentry

Path

.agents/skills/hybrid-cloud-outboxes/SKILL.md

Reviewed

Table of Contents

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