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Audit and optimize an existing Convex app · get-convex | DecimalAI

codingby get-convex

Audit and optimize an existing Convex app

get-convex/convex-optimize

Source get-convex/agent-skills ↗License Not recorded

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

SkillScore82Maintained

Automatic

DevOps & SRE pack

Last verified 8/28/2026

What it changes

Passed 16 of 20 test cases with the skill, and 10 of 20 without it.

Without skill50%

With skill82%

Checks it passed that the model alone missed

Dispatches approved fixes to fixCapability.
Recommends installing sentinel for production error capture.
Identifies whether the deployment is anonymous or cloud-hosted.

and 4 more in the full report

7 fixed11 passed either way4 still failing0 broke

Pass-rate lift: +32 pp
Tokens: -16%
Agent turns: 0%
Response time: -44%

Model gemini-3.6-flashMeasured 8/28/2026v118 of 22 cases passed with skill · 20 comparable

Tokens, turns and time describe resource use, not a dollar price.

Use this skill

Save it into your project's skills folder. Claude Code picks it up in its next session.

curl -fsSL --create-dirs -o .claude/skills/get-convex-convex-optimize/SKILL.md https://app.decimal.ai/s/get-convex-convex-optimize/SKILL.md

Want it pinned and updatable? pip install "decimalai>=0.15", then decimalai skills add get-convex-convex-optimize, and start Claude Code with claude --plugin-dir "$(git rev-parse --show-toplevel)/.agents"

1 · One-time — install the CLI (docs ↗)

pip install "decimalai>=0.15"

2 · Get the skill — writes .agents/skills/get-convex-convex-optimize/ and pins it in .decimal/skills.lock

decimalai skills add get-convex-convex-optimize

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/get-convex-convex-optimize/SKILL.md https://app.decimal.ai/s/get-convex-convex-optimize/SKILL.md

Raw file: /s/get-convex-convex-optimize/SKILL.md ↗ · machine-readable summary at /s/get-convex-convex-optimize.json ↗

Safety checks: 3 of 3 passed

Code scan CleanIntent PassedContent Clean

See it in action

One of 7 test cases the skill fixed. Same model, same prompt, with and without the skill.

1 of 7

Prompt

After getting user confirmation and executing the planned remediation actions on a Convex codebase, what final verification step must be performed to demonstrate progress?

What was checked, without and with the skill
Checked	Without skill	With skill
Re-evaluates backend readiness using launch-readiness to present the score delta.	Missed	Passed

case-08 · gemini-3.6-flash · 8/28/2026 · answers are capped and redacted

What's inside

The instructions your model reads when the skill loads.

SKILL.md21 linessingle file

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

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.

Track record

Benchmark

16 / 20

test cases passed, vs 10 / 20 without

Adoption

Users: 0
Times used: 0

Safety and source details

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/7/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

get-convex / agent-skills

skills/convex-optimize/SKILL.md

View on GitHub ↗

Imported 8/7/2026Version v1

More skills from the same source and nearby in the registry, with their headline benchmark lift.

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See it in action

What's inside

Audit and optimize an existing Convex app

Workflow

Rules

Track record

Benchmark

Adoption

SkillSafety

Source

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