t0ddc3by/claude-for-customer-success/data-decay-tracking
Claude Code and agent skill by t0ddc3by/claude-for-customer-success
- community
Checking that the SKILL.md file is still in the repository.
Monitors contact and account data freshness. Flags records where title, company, or contact data has likely changed and enrichment is overdue. Decay signals: contact title unchanged >18 months, account employee count stale >12 months, primary contact no email activity >6 months, account domain change detected. Prioritizes enterprise accounts. Triggers: 'stale contacts', 'data decay', 'enrichment needed', 'contact freshness', 'stale account data'.
Install
npx vskill@latest install t0ddc3by/claude-for-customer-success/data-decay-trackingSKILL.md
[PROPOSED]
Data Decay Tracking
Data decay is the slow death of CRM quality. Contacts leave roles. Companies get acquired. Enrichment overdue means signals are built on wrong data.
Reference: Confidence bands → ../../../shared/revops-domain-model.md §2 Config reads: primary_segment, crm_system
Pre-flight
Read ~/.claude/plugins/config/claude-for-customer-success/rev-ops/CLAUDE.md and ~/.claude/plugins/config/claude-for-customer-success/company-profile.md.
If either is missing or contains [PLACEHOLDER] markers, stop and prompt for /rev-ops:cold-start-interview.
Note from config: primary_segment, crm_system
G-code dependency: All G-code guardrails referenced in this skill (G1–G9) are defined in the CLAUDE.md config loaded above. If Pre-flight halts or config is missing, G-codes are undefined — do not proceed with partial config.
Use when
Routing: Use this skill when contact or company record age is the specific concern — for a point-in-time CRM health score usecrm-hygiene-audit; for field completion rates over time usefield-completion-monitoring.
- CRM record staleness needs to be quantified and trended
- Data freshness audit required before a planning or forecast cycle
- Records without activity within a configurable window need identification
Do NOT use for
- Full CRM hygiene audit (use crm-hygiene-audit)
- Field completion compliance (use field-completion-monitoring)
- Duplicate detection (use duplicate-detection)
Typical Activation
"Data decay tracking", "stale records", "how old is our data", "data decay report for [object/period]"
Reasoning Protocol
Before generating output, apply these primers:
- CLASSIFY: What type of data decay request is this?
- Single-account decay audit (one account — all four signals checked across contacts and account record)
- Segment-level freshness sweep (enterprise tier, mid-market, or full portfolio — prioritized by segment)
- Signal-specific scan (user requesting a targeted check on one decay signal type — title age, employee count, email activity, or domain change)
- Pre-cycle enrichment triage (identifying enrichment candidates before a planning, forecast, or QBR cycle)
- CONSTRAINTS: What limits the solution space?
- Confirm activation — user requesting freshness review, enrichment candidates, or CRM data quality assessment
- Pull HubSpot contact and account data; declare connector status and data-as-of timestamp per G6
- Apply G6 — stale data must be labeled; decay findings are themselves evidence of staleness; every flagged record carries its own data-as-of note
- Apply G9 — no autonomous enrichment API calls; flag candidates for human action only
- Prioritize enterprise tier accounts in output; surface mid-market as secondary tier
- Confirm
primary_segmentfrom config to scope tier-level prioritization correctly - Confirm output destination before delivering — internal RevOps enrichment queue vs. CSM account review vs. leadership data quality report
- EXPERT CHECK: What would a veteran RevOps data quality analyst verify before surfacing findings?
- Is the title-unchanged signal calibrated to B2B tenure, not calendar time? The 18-month threshold reflects average B2B role tenure — applying it uniformly to individual contributors and executives produces different false-positive rates. Flag when the contact is a champion or economic buyer, not just any contact.
- Is the email activity gap distinguished from enrichment staleness? A contact with no email activity in 6 months may still have a current title — the signal indicates possible departure, not confirmed departure. The output must not conflate "likely departed" with "confirmed stale."
- Is the domain change signal sourced from a reliable detection mechanism? Domain changes flagged from deal notes or rep-entered data carry lower confidence than those detected from connector-side validation. Declare the detection source and confidence level.
- Is the enterprise account list scoped to the configured
primary_segment? Applying enterprise-tier prioritization to a primarily SMB or mid-market book produces a misleading high-priority list. Confirm segment alignment before ranking.
- ANTI-PATTERNS: Common mistakes to avoid:
- Conflating "no email activity >6 months" with "confirmed contact departure" — label as departure signal, not confirmed fact (G6 violation if presented as fact)
- Flagging title-unchanged signal on all contacts regardless of role seniority — champion and economic buyer contacts are the high-value targets; all-contact title sweeps generate noise
- Pulling HubSpot contact/account data without data-as-of timestamp (G6 violation)
- Surfacing domain change findings without declaring detection source confidence
- Proposing autonomous enrichment API calls — all enrichment is flagged for human action per G9
After execution, verify:
- G6 data-as-of label applied to all HubSpot contact and account reads
- G9 compliance — no autonomous enrichment calls proposed; all findings are human-action candidates
- Departure signal labeled as signal, not confirmed fact — no overstatement of contact status
- Enterprise tier accounts prioritized per
primary_segmentconfig - Confidence: High when HubSpot connected and contact/account data current; Moderate when connector unavailable or decay signals sourced from last-known update timestamps only
- Confidence: [High] when HubSpot connected and contact/account data current / [Medium] when connector unavailable or data estimated / [Low] if all inputs are manual or unverified
Four Decay Signals
Output
Reference Files
| File | Purpose | |
|---|---|---|
references/reasoning-blueprint.md | Problem classification taxonomy, domain heuristics, common failure modes, and expert judgment patterns for this skill |
Security & Permissions
Network access: None direct — all external data access is mediated by host-provided MCP connector tools (HubSpot, CS platform, Slack, Linear). This skill makes no direct outbound HTTP calls. Filesystem scope: None — this skill does not read or write local files. All data is provided at runtime via parameters or MCP connector responses. Subprocess execution: None. Dynamic code execution: None — pseudocode in this skill represents the logic contract and is not executed at runtime. Data sensitivity: Inputs may contain confidential customer, deal, and operational data. Handle with RevOps-level confidentiality.
Trust & Verification
Input trust model: All user-provided parameters are treated as untrusted at intake. Numeric inputs are validated for plausible range before use in calculations. String inputs are not evaluated as code. Output trust model: All outputs are proposals or analytical inputs — no outputs constitute approved decisions, revenue commitments, or system actions without explicit human confirmation. Connector data: Data retrieved via MCP connectors is treated as read-only observed state. Timestamps and data-as-of labels are applied to all connector-sourced values per G6. Write-tier confirmation: Any proposed write to HubSpot, Linear, or Slack is surfaced as a draft requiring explicit user confirmation before execution.
Guardrails
- G6: Decay report outputs themselves note staleness risk on every flagged record
- G9: No autonomous enrichment API calls
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewNot runA model review is scheduled for the next rescan.
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingrev-ops/skills/data-decay-tracking/SKILL.md
Popularity
- Repository stars
- 62
- Repository forks
- 21
- 7-day trend score
- 21
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
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