affaan-m/ECC
Evidence-first automation inventory and overlap audit workflow for ECC. Use when the user wants to know which jobs, hooks, connectors, MCP servers, or wrappers are live, broken, redundant, or missing before fixing anything.
npx skills add https://github.com/affaan-m/ECC --skill "skills/automation-audit-ops"Source checked Jul 28, 2026·Refresh due Oct 26, 2026
Reorganized from the pinned upstream SKILL.md
According to the pinned SKILL.md from affaan-m/ECC: Use this when the user asks what automations are live, which jobs are broken, where overlap exists, or what tooling and connectors are actually doing useful work right now.
npx skills add https://github.com/affaan-m/ECC --skill "skills/automation-audit-ops"Best fit
Bring this context
Expected outputs
Key source sections
Sections are extracted automatically from the pinned SKILL.md and link back to the source.
Read the current live surface before theorizing:
important claims cite a live proof path
Pull these ECC-native skills into the workflow when relevant:
user asks "what automations do I have", "what is live", "what is broken", or "what overlaps"
start read-only unless the user explicitly asked for fixes
SkillSignal prompt templates
These prompts were written by SkillSignal from the source structure; they are not upstream text.
Task-start prompt
Confirm source fit, inputs, and outputs before acting.
Use automation-audit-ops to help me with: [specific task]. Context: [files, data, or background]. Constraints: [environment, scope, and prohibited actions]. Before acting, check the pinned SKILL.md and explain which sections apply, what inputs are still missing, and what you will deliver.
Source-guided execution
Make the Agent explicitly follow the key extracted sections.
Apply the pinned automation-audit-ops source to [task]. Pay particular attention to these source sections: “Workflow”, “Verification”, “Skill Stack”, “When to Use”, “Guardrails”. Preserve the important decision at each step. Mark facts not covered by the source as “needs confirmation” instead of inventing them. Then verify the result against my acceptance criteria: [criteria].
Result-review prompt
Check omissions, permissions, and source drift before delivery.
Review the current automation-audit-ops result: (1) does it satisfy the original task; (2) were any applicable steps or limits in the pinned SKILL.md missed; (3) did it perform any unauthorized file, command, network, or data action; and (4) which conclusions remain unverified? List issues first, then fix only what the source or user authorization supports.
Output checklist
The task matches the purpose documented in the SKILL.md.
The source section “Workflow” has been checked.
The source section “Verification” has been checked.
The source section “Skill Stack” has been checked.
The source section “When to Use” has been checked.
Inputs, constraints, and acceptance criteria are explicit.
Unverified facts, compatibility, and outcome claims are clearly marked.
Any file, command, network, or data action has been reviewed.
Choose a different workflow
ECC用の証拠ベースの自動化インベントリとオーバーラップ監査ワークフロー。ユーザーがどのジョブ、フック、コネクタ、MCPサーバー、またはラッパーがライブか、壊れているか、冗長であるか、修正前に不足しているかを知りたい場合に使用します。
A separate implementation from affaan-m/ECC; compare its source, maintenance signals, and permission requirements.
Open source detail面向ECC的以证据为先的自动化清单与重叠审计工作流。当用户希望在修复任何内容之前了解哪些作业、钩子、连接器、MCP服务器或包装器是活跃的、损坏的、冗余的或缺失时使用。
A separate implementation from affaan-m/ECC; compare its source, maintenance signals, and permission requirements.
Open source detailUse when the user says "review the design", "check the UI", or wants a comprehensive UI/UX review. Uses a 7-phase methodology covering interaction, responsiveness, accessibility, and more.
A separate implementation from event4u-app/agent-config; compare its source, maintenance signals, and permission requirements.
Open source detailFAQ
Use this when the user asks what automations are live, which jobs are broken, where overlap exists, or what tooling and connectors are actually doing useful work right now.
The catalog detected this source-specific install command: npx skills add https://github.com/affaan-m/ECC --skill "skills/automation-audit-ops". Inspect the command and pinned source before running it.
No dedicated Agent platform is declared in the pinned source record.
Quality breakdown
Based on traceable docs and repository signals; stars are not treated as quality.
Compare before choosing
These links are selected from shared tasks, functions, stacks, platforms, and same-name variants. Compare the source owner, documentation, permissions, and maintenance signals.
ECC用の証拠ベースの自動化インベントリとオーバーラップ監査ワークフロー。ユーザーがどのジョブ、フック、コネクタ、MCPサーバー、またはラッパーがライブか、壊れているか、冗長であるか、修正前に不足しているかを知りたい場合に使用します。
面向ECC的以证据为先的自动化清单与重叠审计工作流。当用户希望在修复任何内容之前了解哪些作业、钩子、连接器、MCP服务器或包装器是活跃的、损坏的、冗余的或缺失时使用。
Use when the user says "review the design", "check the UI", or wants a comprehensive UI/UX review. Uses a 7-phase methodology covering interaction, responsiveness, accessibility, and more.
Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.
Medicinal chemistry filters for compound triage. Apply drug-likeness rules (Lipinski, Veber, CNS), structural alert catalogs (PAINS, NIBR, ChEMBL), complexity metrics, and the medchem query language for library filtering.
Use this when the user asks what automations are live, which jobs are broken, where overlap exists, or what tooling and connectors are actually doing useful work right now.
This is an audit-first operator skill. The job is to produce an evidence-backed inventory and a keep / merge / cut / fix-next recommendation set before rewriting anything.
Pull these ECC-native skills into the workflow when relevant:
workspace-surface-audit for connector, MCP, hook, and app inventoryknowledge-ops when the audit needs to reconcile live repo truth with durable contextgithub-ops when the answer depends on CI, scheduled workflows, issues, or PR automationecc-tools-cost-audit when the real problem is webhook fanout, queued jobs, or billing burn in the sibling app reporesearch-ops when local inventory must be compared against current platform support or public docsverification-loop for proving post-fix state instead of relying on assumed recoveryRead the current live surface before theorizing:
Group them by surface:
For every surfaced automation, mark:
Then classify the problem type:
Back every important claim with a concrete source:
If the current state is ambiguous, say so directly instead of pretending the audit is complete.
For each overlapping or suspect surface, return one call:
The value is in collapsing noisy automation into one canonical ECC lane, not in preserving every historical path.
CURRENT SURFACE
- automation
- source
- live state
- proof
FINDINGS
- active breakage
- overlap
- stale status
- missing capability
RECOMMENDATION
- keep
- merge
- cut
- fix next
NEXT ECC MOVE
- exact skill / hook / workflow / app lane to strengthen