Source-declared outputs
- HTTP timing and response headers;
- provider freshness timestamp;
- queue or job state;
affaan-m/ECC
latency-critical-systems
Use for latency-sensitive systems such as realtime dashboards, market data, streaming agents, execution gateways, queues, caches, or HFT-like infrastructure where freshness and p95 latency matter.
68Collecting
See how to use itView GitHub source
npx skills add https://github.com/affaan-m/ECC --skill "skills/latency-critical-systems"Automated source guideGeneral workflowStandard source
Source checked Jul 28, 2026·Refresh due Oct 26, 2026
Reorganized from the pinned upstream SKILL.md
Source-grounded usage guide: latency-critical-systems
Use this skill when the user cares about realtime behavior, hot paths, streaming freshness, or execution speed. This includes HFT-like infrastructure, but the skill is engineering-focused. It does not authorize live trading or financial advice.
npx skills add https://github.com/affaan-m/ECC --skill "skills/latency-critical-systems"The pinned source supports a structured brief, but not an expanded tutorial. Only detected inputs, outputs, and sections are shown.
288 source words · 5 usable sections
Source workflow
Read latency-critical-systems through these 4 source sections
Sections are extracted automatically from the pinned SKILL.md and link back to the source.
Verification
Use live readbacks when a deployed surface exists:
HTTP timing and response headers;provider freshness timestamp;queue or job state;
Split The Metrics
Do not collapse everything into "fast." Track:
p50, p95, and p99 latency;throughput;freshness age;
Map The Hot Path
Write the path from user/event to final visible state:
Write the path from user/event to final visible state:Then measure each segment separately.
Optimization Order
1. Remove unnecessary round trips. 2. Cache stable reads with freshness metadata. 3. Batch small calls and writes. 4. Move compute closer to the data or the user. 5. Split hot and cold paths. 6. Apply backpressure before queues grow unbounded. 7. Use streaming only when it impro…
Remove unnecessary round trips.Cache stable reads with freshness metadata.Batch small calls and writes.
Source checklist
Verify each item before delivery
The source section “Verification” has been checked.
The source section “Split The Metrics” has been checked.
The source section “Map The Hot Path” has been checked.
The source section “Optimization Order” has been checked.
Source output checked: HTTP timing and response headers;
Source output checked: provider freshness timestamp;
FAQ
What does the latency-critical-systems source document cover?
Use this skill when the user cares about realtime behavior, hot paths, streaming freshness, or execution speed. This includes HFT-like infrastructure, but the skill is engineering-focused. It does not authorize live trading or financial advice.
How do I install latency-critical-systems?
The source record exposes this install command: npx skills add https://github.com/affaan-m/ECC --skill "skills/latency-critical-systems". Inspect the command and pinned source before running it.
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View original Skill.mdThis page is parsed directly from the repository SKILL.md without editorial rewriting. Collected: Jul 28, 2026 · about 2 min
Latency Critical Systems
Use this skill when the user cares about realtime behavior, hot paths, streaming freshness, or execution speed. This includes HFT-like infrastructure, but the skill is engineering-focused. It does not authorize live trading or financial advice.
Split The Metrics
Do not collapse everything into "fast." Track:
- p50, p95, and p99 latency;
- throughput;
- freshness age;
- queue depth;
- cache hit rate;
- provider/API response time;
- browser render time;
- correctness under load;
- failure and retry behavior.
Map The Hot Path
Write the path from user/event to final visible state:
source event -> provider API -> ingest worker -> queue -> cache -> edge route
-> client stream -> browser render -> user-visible state
Then measure each segment separately.
Optimization Order
- Remove unnecessary round trips.
- Cache stable reads with freshness metadata.
- Batch small calls and writes.
- Move compute closer to the data or the user.
- Split hot and cold paths.
- Apply backpressure before queues grow unbounded.
- Use streaming only when it improves freshness or user experience.
- Add canaries for stale data, degraded providers, and bad cache state.
Verification
Use live readbacks when a deployed surface exists:
- HTTP timing and response headers;
- provider freshness timestamp;
- queue or job state;
- edge/cache state;
- browser verification for actual UI freshness;
- logs around retries and degraded mode.
For market-data or execution-adjacent paths, also verify orderbook age, VWAP assumptions, provider status, and kill-switch behavior before calling the path ready.
Guardrails
- Do not optimize latency by dropping required validation.
- Do not hide stale data behind fast cache hits.
- Do not claim millisecond behavior from client labels without measurement.
- Do not run live orders, destructive migrations, or customer-impacting deploys without an explicit approval gate.
- Keep secrets and private payloads out of logs and benchmark artifacts.
- Source repo
- affaan-m/ECC
- Skill path
- skills/latency-critical-systems/SKILL.md
- Commit SHA
- 4e973d3eaf92
- Repository license
- MIT
- Data collected