본문으로 건너뛰기
cccskills
무료GitHub에 공개

managing-anecdotes

Use when working with Anecdotes — anecdotes compliance automation platform for managing security programs, controls, evidence, and multi-framework compliance. Covers control monitoring, evidence automation, plugin integrations, gap analysis, and audit readiness. Use when reviewing compliance status across frameworks, tracking evidence collection, analyzing control gaps, or preparing for security compliance audits.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

설치 방법 보기

포함된 파일(1)

  • SKILL.md7.3 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Anecdotes Management Skill

Manage and analyze Anecdotes compliance controls, evidence, plugins, and audit readiness.

API Conventions

Authentication

All API calls use Authorization: Bearer $ANECDOTES_API_TOKEN -- injected automatically. Never hardcode tokens.

Base URL

https://api.anecdotes.ai/v1

Core Helper Function

#!/bin/bash

anecdotes_api() {
    local method="$1"
    local endpoint="$2"
    local data="${3:-}"

    if [ -n "$data" ]; then
        curl -s -X "$method" \
            -H "Authorization: Bearer $ANECDOTES_API_TOKEN" \
            -H "Content-Type: application/json" \
            "https://api.anecdotes.ai/v1${endpoint}" \
            -d "$data"
    else
        curl -s -X "$method" \
            -H "Authorization: Bearer $ANECDOTES_API_TOKEN" \
            -H "Content-Type: application/json" \
            "https://api.anecdotes.ai/v1${endpoint}"
    fi
}

Output Rules

  • TOKEN EFFICIENCY: Extract only needed fields with jq
  • Target <=50 lines per script output
  • Never dump full API responses

Discovery Phase

#!/bin/bash
echo "=== Frameworks ==="
anecdotes_api GET "/frameworks" \
    | jq -r '.data[] | "\(.id)\t\(.name)\t\(.status)"' | column -t | head -10

echo ""
echo "=== Controls Overview ==="
anecdotes_api GET "/controls?limit=1" \
    | jq '"Total controls: \(.meta.total // "N/A")"' -r

echo ""
echo "=== Plugins (Integrations) ==="
anecdotes_api GET "/plugins" \
    | jq -r '.data[] | "\(.name)\t\(.status)\t\(.type)"' | column -t | head -10

Analysis Phase

Control Status

#!/bin/bash
echo "=== Controls by Status ==="
CONTROLS=$(anecdotes_api GET "/controls?limit=200")
echo "$CONTROLS" | jq '{
    total: (.data | length),
    met: ([.data[] | select(.status == "met")] | length),
    not_met: ([.data[] | select(.status == "not_met")] | length),
    partially_met: ([.data[] | select(.status == "partially_met")] | length),
    not_applicable: ([.data[] | select(.status == "not_applicable")] | length)
}'

echo ""
echo "=== Unmet Controls ==="
echo "$CONTROLS" | jq -r '.data[] | select(.status == "not_met") | "\(.status)\t\(.name[0:50])\t\(.framework[0:15])"' \
    | column -t | head -15

echo ""
echo "=== Control Coverage ==="
echo "$CONTROLS" | jq -r '[.data[] | {fw: .framework, status: .status}] | group_by(.fw) | map({framework: .[0].fw[0:20], total: length, met: ([.[] | select(.status == "met")] | length)}) | .[] | "\(.framework)\t\(.met)/\(.total)\t\((.met * 100 / .total | floor))%"' | column -t

Evidence Tracking

#!/bin/bash
echo "=== Evidence Summary ==="
anecdotes_api GET "/evidence?limit=200" \
    | jq '{
        total: (.data | length),
        collected: ([.data[] | select(.collectionStatus == "collected")] | length),
        pending: ([.data[] | select(.collectionStatus == "pending")] | length),
        failed: ([.data[] | select(.collectionStatus == "failed")] | length)
    }'

echo ""
echo "=== Failed Evidence Collection ==="
anecdotes_api GET "/evidence?limit=50&collectionStatus=failed" \
    | jq -r '.data[] | "\(.controlName[0:30])\t\(.name[0:35])\t\(.source // "manual")"' \
    | column -t | head -15

Plugin Health

#!/bin/bash
echo "=== Plugin Status ==="
anecdotes_api GET "/plugins" \
    | jq -r '.data[] | "\(.status)\t\(.name[0:25])\t\(.type)\tlastSync:\(.lastSyncTime[0:16] // "Never")"' \
    | sort | column -t | head -20

echo ""
echo "=== Disconnected Plugins ==="
anecdotes_api GET "/plugins" \
    | jq -r '.data[] | select(.status != "connected") | "\(.name)\t\(.status)\terror:\(.lastError[0:40] // "N/A")"' | column -t

Gap Analysis

#!/bin/bash
FRAMEWORK_ID="${1:-}"

echo "=== Framework Gap Analysis ==="
ENDPOINT="/controls?limit=200"
[ -n "$FRAMEWORK_ID" ] && ENDPOINT="/frameworks/${FRAMEWORK_ID}/controls?limit=200"

anecdotes_api GET "$ENDPOINT" \
    | jq -r '.data[] | select(.status == "not_met" or .status == "partially_met") | "\(.status)\t\(.name[0:45])\t\(.evidenceCount) evidence items"' \
    | column -t | head -20

echo ""
echo "=== Controls Without Evidence ==="
anecdotes_api GET "$ENDPOINT" \
    | jq -r '.data[] | select(.evidenceCount == 0 and .status != "not_applicable") | "\(.name[0:50])\t\(.framework[0:15])\tno evidence"' \
    | column -t | head -10

Output Format

Present results as a structured report:

Managing Anecdotes Report
═════════════════════════
Resources discovered: [count]

Resource       Status    Key Metric    Issues
──────────────────────────────────────────────
[name]         [ok/warn] [value]       [findings]

Summary: [total] resources | [ok] healthy | [warn] warnings | [crit] critical
Action Items: [list of prioritized findings]

Target ≤50 lines of output. Use tables for multi-resource comparisons.

Anti-Hallucination Rules

  1. NEVER assume resource names — always discover via CLI/API in Phase 1 before referencing in Phase 2.
  2. NEVER fabricate metric names or dimensions — verify against the service documentation or --help output.
  3. NEVER mix CLI commands between service versions — confirm which version/API you are targeting.
  4. ALWAYS use the discovery → verify → analyze chain — every resource referenced must have been discovered first.
  5. ALWAYS handle empty results gracefully — an empty response is valid data, not an error to retry.

Counter-Rationalizations

ShortcutCounterWhy
"I'll skip discovery and check known resources"Always run Phase 1 discovery firstResource names change, new resources appear — assumed names cause errors
"The user only asked for a quick check"Follow the full discovery → analysis flowQuick checks miss critical issues; structured analysis catches silent failures
"Default configuration is probably fine"Audit configuration explicitlyDefaults often leave logging, security, and optimization features disabled
"Metrics aren't needed for this"Always check relevant metrics when availableAPI/CLI responses show current state; metrics reveal trends and intermittent issues
"I don't have access to that"Try the command and report the actual errorAssumed permission failures prevent useful investigation; actual errors are informative

Common Pitfalls

  • Plugin-driven evidence: Most evidence is auto-collected via plugins -- check plugin health first
  • Multi-framework mapping: Controls can map to multiple frameworks simultaneously
  • Pagination: Use limit and offset parameters -- check meta.total
  • Rate limits: Check response headers for rate limiting information
  • Evidence freshness: Auto-collected evidence has expiry -- check collection timestamps

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Cloudflare GraphQL Analytics for zone traffic, firewall events, Workers metrics, and schema exploration. Use when querying Cloudflare analytics data or exploring the GraphQL API.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

cloudthinker-ai/CloudSkills62026년 4월 5일 업데이트

Use when working with Alloydb — google AlloyDB instance analysis, query insights, columnar engine optimization, maintenance windows, and cluster health.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

cloudthinker-ai/CloudSkills62026년 4월 5일 업데이트

Use when working with Aqua — aqua Security platform analysis. Covers container runtime protection, image assurance policies, compliance frameworks, vulnerability management, workload protection, and registry scanning. Use when analyzing container security posture, reviewing image compliance, investigating runtime alerts, or auditing security policies.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

cloudthinker-ai/CloudSkills62026년 4월 5일 업데이트

Use when working with Bigquery — google BigQuery job analysis, slot utilization, cost analysis, dataset management, and query optimization.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

cloudthinker-ai/CloudSkills62026년 4월 5일 업데이트

Use when working with Cassandra — apache Cassandra keyspace analysis, compaction strategies, repair status, nodetool operations, and cluster health monitoring.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

cloudthinker-ai/CloudSkills62026년 4월 5일 업데이트

Use when working with Checkov — checkov infrastructure-as-code security scanning. Covers Terraform, CloudFormation, Kubernetes, and Dockerfile scanning, policy management, custom checks, compliance frameworks, and suppression management. Use when scanning IaC for security misconfigurations, evaluating compliance, managing custom policies, or reviewing scan results.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

cloudthinker-ai/CloudSkills62026년 4월 5일 업데이트

cloudthinker-ai의 스킬 모두 보기

이 스킬의 문제 신고