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Convex Optimize · get-convex/agent-skills · Skills Docs

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get-convex/agent-skills

Issue No. 46 · Convex Optimize

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Convex Add
Convex Advisor
Convex Agent
Convex Auth
Convex Authz
Convex Backup
Convex Billing
Convex Cost
Convex Create Component
Convex Crons
Convex Deploy Guard

33 chapters · 70 min

24 / 33Convex Optimize

Skills

Chapter 24 of 33

Convex Optimize

Audit and optimize an existing Convex app: security, scale, upgrades, observability.

1 minute · 276 words · 3 sections

Audit and optimize an existing Convex app

The remediation WORKFLOW for an existing app: open with a scored assessment, then act on it — upgrade stale components and set up observability — plan-then-confirm-then-apply. The assessment itself is delegated to launch-readiness (the findings-bus scorer); optimize’s distinct value is the actions it takes on the result.

Workflow

On this page

Audit and optimize an existing Convex app
Workflow
Rules

This chapter

Position: 24 of 33
Reading time: 1 min
Words: 276

Source

View SKILL.md(opens in a new tab)

Convex Design

14Convex Domains

16Convex Expert

17Convex Explain App

18Convex Improve Convex Plugin

19Convex Insights

20Convex Launch Readiness

21Convex Migrate Rehearse

22Convex Migrate

23Convex Monitor

24Convex Optimize

25Convex Quickstart

26Convex Reviewer

28Convex Self Heal

29Convex Sentinel

30Convex Suggest

32Convex Verify

Detect the app: a convex/ directory, the schema, and whether it’s an anonymous or cloud deployment.
ASSESS via launch-readiness — one scored, deduped report across authz/reviewer/advisor/insights with an ordered fix plan. Do not re-run those passes by hand; optimize consumes launch-readiness’s report rather than re-implementing the audit.
UPGRADE: run check-updates against the pinned @convex-dev/* components and fold stale-component (staleness-class) findings into the same plan.
OBSERVABILITY: if the readiness report flagged an observability gap (no prod error capture), offer to install sentinel.
Present the combined prioritized plan — the launch-readiness score + the fix plan + upgrades + observability, security/data-loss first — and apply only on explicit confirmation, dispatching each fix to its fixCapability.
After applying, re-run the launch-readiness assessment and show the score delta.

Rules

Read-only first. Present a plan and CONFIRM before changing any file.
Delegate the audit to launch-readiness (the findings-bus scorer); don’t re-implement reviewer/advisor/insights inline — optimize’s job is acting on the report (upgrades + observability), not re-scoring.
Prioritize security and data-loss risks above style, following launch-readiness’s ordering.
Never auto-land changes on someone’s existing prod app; re-assess after applying and show the score moved.

Install this repository

$ npx skills add get-convex/agent-skills

Skills install per repository, not per chapter — the CLI has no documented per-skill form, so we do not print one.

Typesetting note

Shifted “3 headings” from h1 to h2 so the chapter title is the only h1.

Agent Skills specification

Chapter 23Convex Monitor Chapter 25Convex Quickstart

Colophon for this issue

Colophon

How this issue was made

Source

github.com/get-convex/agent-skills, branch main, last pushed 4 August 2026.

Licence

All rights reserved — view on GitHub — with no detectable licence, this issue links rather than republishes: the chapters are omitted from the agent manifest and from the whole-book markdown.

Discovery

33 chapters found by walking the repository tree for SKILL.md, not by matching a directory convention. One layout observed: skills/*/SKILL.md.

Issue colours

Resolved from a deterministic hash of the owner name. Two accent tones are generated per issue and each is proven against its own ground before it ships: a single accent that passes AA on both light and dark paper is arithmetically impossible.

Heading repairs

1 repair applied to this chapter so the document has one h1 and no skipped levels:

Shifted “3 headings” from h1 to h2 so the chapter title is the only h1.

Spec compliance

Every chapter satisfies the Agent Skills specification’s frontmatter rules.

Images

Images inside a chapter come from the upstream repository. Where the author gave no alternative text we mark the image decorative rather than inventing a description — a plausible caption we made up is worse than none for the reader who depends on it.

Signal

Install counts come from skills.sh. They measure downloads, not quality, and an unranked repository is not an unread one.

Agent surfaces

The whole issue is available as one markdown document at /get-convex/agent-skills.md, and each chapter at its own .md URL.

Publication

Set by Skills Docs from the source repository. Body text is Literata at the reader’s chosen size and measure; code is Geist Mono. Nothing on this page was written by us except this paragraph.

get-convex/agent-skills

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Markdown for agents