Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/luanpdd/kit-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/luanpdd/kit-mcp/sre)<a href="https://agentmods.dev/commands/luanpdd/kit-mcp/sre"><img src="https://agentmods.dev/badge/commands/luanpdd/kit-mcp/sre.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00055 | $0.03125 |
| Opus 5 | $0.00028 | $0.01563 |
| Sonnet 5 | $0.00011 | $0.00625 |
| Haiku 4.5 | $0.00006 | $0.00313 |
Grade A, and why
sre scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 231 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Subcomandos cobrem cap 3, 5, 6, 15, 32 do livro Google SRE:
golden-signals— 4 signals universais (cap 6)auditar-toil/audit-toil— eliminating toil (cap 5)postmortem— blameless postmortem (cap 15)prr— Production Readiness Review (cap 32)risk-budget/budget— risk continuum (cap 3)
Cria/Atualiza: o que cada agent invocado cria (patches OTel, TOIL-AUDIT.md, postmortem, PRR-REPORT.md, snapshot risk-budget).
Após: o usuário tem o output do agent (instrumentação aplicada, audit, postmortem revisável, PRR scored, ou snapshot de budget).
<execution_context>
Skills consultadas pelos agents (Phase 36): kit/skills/sre-risk-management/SKILL.md, kit/skills/four-golden-signals/SKILL.md, kit/skills/eliminating-toil/SKILL.md, kit/skills/blameless-postmortems/SKILL.md, kit/skills/production-readiness-review/SKILL.md + glossário em kit/skills/_shared-sre/glossary.md.
Agents disponíveis (Phase 37):
golden-signals-instrumenter— AGCORE-SRE-01toil-auditor— AGCORE-SRE-02postmortem-writer— AGCORE-SRE-03prr-conductor— AGCORE-SRE-04
Subcomando risk-budget é caso especial — comando direto (Plan 05 não usa agent); orquestrador delega aplicando skill sre-risk-management inline ou re-encaminhando para /risk-budget.
</execution_context>
Subcomandos suportados (sinônimos PT-BR/EN):
| Subcomando | Sinônimos | Agent dispatched | Cap livro |
|---|---|---|---|
golden-signals |
signals, 4signals, golden |
golden-signals-instrumenter |
6 |
auditar-toil |
audit-toil, toil, auditar |
toil-auditor |
5 |
postmortem |
pm, post-mortem |
postmortem-writer |
15 |
prr |
production-readiness, readiness-review |
prr-conductor |
32 |
risk-budget |
budget, risk, continuum |
(comando direto — /risk-budget) |
3 |
cascading |
cascade, cascading-failures, auditar-cascading |
cascading-failures-auditor |
22 (v1.11) |
load-shedding |
shed, load-shed, loadshedding |
load-shedding-instrumenter |
22 (v1.11) |
release |
auditar-release, release-audit, pipeline |
release-pipeline-auditor |
8 (v1.11) |
help |
ajuda, ? |
exibe esta tabela inline | — |
Roteamento de flags por subcomando:
golden-signals <target>— args passados como<target>+ flags--service--saturation--runtimeauditar-toil— flags--time-window--team-size--output--runbooks-pathspostmortem— flags mutuamente exclusivas--from-investigation <id>OU--incident "<desc>"+--severityprr— flags mutuamente exclusivas--service <name>OU--feature "<desc>"+--engagement--reviewerrisk-budget—[<slo_name>]opcional +--format--explain
Exemplos:
/sre golden-signals supabase/functions/process-emails # instrumentar Edge Function
/sre auditar-toil --time-window 6m # audit toil últimos 6 meses
/sre postmortem --from-investigation incident-2026-05-06-1432-checkout-burn # continuação de v1.9
/sre prr --service orders-api --reviewer @sre-lead # PRR de serviço existente
/sre risk-budget checkout_success --explain # budget + sabedoria 99.99% inline
/sre help # exibe tabela de subcomandos
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 231 lines · 55 tokens per session scan A eb4701d8d5fd
sre is a command published in the GitHub repository luanpdd/kit-mcp (1 stars, last pushed yesterday), licensed MIT. It adds 55 tokens to every session and 3,125 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.