content-decay

name	content-decay
description	Use when: kullanıcı "içerik decay", "content decay", "tıklama düşen sayfalar", "ctr düştü", "90 gün öncesine göre azalma", "trafik kaybeden sayfalar", "decay analizi", "content_decay sheet yenile" der ya da /pseo-content-decay çağırır. Also use when: aktif projenin GSC verisi master.xlsx'te mevcut (gsc-pull önce çalışmış); 90-günlük recent + previous pencere karşılaştırması yapılacak; pillar bazlı içerik decay haritası lazım; downstream content-improve / new-content-plan skill'leri bu listeyi tüketecek. Do not use when: quick-win opportunity scoring (quick-wins skill), GSC delta ingestion (gsc-pull skill), tek-URL audit (tech-audit skill), cannibalization analizi — ayrı discovery skill'leri. Master.xlsx yokken çağırma; init-project + gsc-pull önce çalışmalı (DURUR #6).
version	1.0
status	active
category	discovery
inputs	{"project_slug":{"type":"string","required":true,"description":"Slug; resolves projects/{slug}/master.xlsx + project.config.json."},"days_back":{"type":"integer","required":false,"default":90,"description":"Recent window length in days; previous window has equal length."},"dimensions":{"type":"array","required":false,"description":"GSC dimensions (default: ['page'])."}}
outputs	["master.xlsx#content_decay","outputs/reports/{date}-content-decay.md","events.jsonl","inbox/gsc/{date}-enhanced_search_analytics-decay-recent-{slug}.json","inbox/gsc/{date}-enhanced_search_analytics-decay-previous-{slug}.json","inbox/dfs/{date}-historical_rank_overview-decay-{slug}.json"]
consumes	["init-project:projects/{slug}/master.xlsx","gsc-pull:master.xlsx#gsc_performance"]
produces	["new-content-plan","drift-check"]
triggers	{"manual":["/pseo-content-decay"],"natural_language":"\"içerik decay\", \"content decay\", \"tıklama düşen sayfalar\", \"ctr düştü\",\n\"90 gün öncesine göre azalma\", \"trafik kaybeden sayfalar\",\n\"decay analizi\", \"content_decay sheet yenile\"\n","hooks":[],"scheduled":[{"cron":"0 7 * * 1","mode":"report-only"}]}
mcp_tools	{"required":["mcp__gsc__enhanced_search_analytics"],"optional":["mcp__dataforseo__dataforseo_labs_google_historical_rank_overview"]}
budget	{"uses_paid_mcp":false,"estimated_credits":0}
autonomy	{"confidence":"HIGH","requires_approval":true,"safe_auto_execute":false}

content-decay — discovery skill (Phase 7 Wave 1)

10-step protocol. Steps map 1:1 to workflow_runner invocations + the spec §16.5 8-step MCP discipline. Raw JSON drift recovery is mandatory: every MCP response is dropped into inbox/gsc/ (or inbox/dfs/ for the optional historical-rank cross-check) before any transform runs, so a transform bug never costs us the upstream payload.

This skill follows the convention authority established by skills/discovery/quick-wins/SKILL.md + the Phase 6 GSC ingestion paterni skills/ingestion/gsc-pull/SKILL.md. The 10-step protocol shape, raw JSON inbox discipline, URL normalization (D-03), DURUR + flag rule, and provenance event format are reused verbatim — only the domain content (window semantics, transform script, target sheet, optional DFS branch) changes. Deviate only with an ADR.

Inputs (frontmatter contract)

Name	Type	Default	Notes
project_slug	string	—	Required. Resolves projects/{slug}/master.xlsx.
days_back	integer	90	Recent window end=today, start=today-N. Previous window same length.
dimensions	array	['page']	GSC dimensions for enhanced_search_analytics calls.

workspace_root is resolved via PSEO_WORKSPACE_ROOT env or explicit test override (mirrors workflow_runner / events_writer).

Outputs (artifacts produced)

• projects/{slug}/master.xlsx#content_decay — per-page recent vs previous window decay rows (8 cols, schema-locked).
• projects/{slug}/outputs/reports/{date}-content-decay.md — human- readable summary (top decayed pages, trend distribution, pillars).
• projects/{slug}/_state/events.jsonl — event_kind=provenance entries (source.kind=gsc_mcp; one per MCP call, plus optionally one dataforseo_mcp entry when the optional rank cross-check fires).
• projects/{slug}/inbox/gsc/{date}-enhanced_search_analytics-decay-recent-{slug}.json — raw MCP payload for the recent 90-day window (drift recovery).
• projects/{slug}/inbox/gsc/{date}-enhanced_search_analytics-decay-previous-{slug}.json — raw MCP payload for the previous 90-day window.
• (optional) projects/{slug}/inbox/dfs/{date}-historical_rank_overview-decay-{slug}.json — raw DFS historical rank cross-check payload (only when the optional branch is invoked AND its budget pre-flight passes).

10-Step Body Protocol

Each step name must match the steps[*].name passed to workflow_runner.create_run. Names are stable identifiers across runs.

Step 1 — create_run

Open a workflow run shell. The state file lives at projects/{slug}/_state/workflows/{run_id}.json (ADR-021, ADR-019).

from scripts.state import workflow_runner
handle = workflow_runner.create_run(
    skill="content-decay",
    project_slug=project_slug,
    steps=[
        {"name": "fetch_recent"},
        {"name": "fetch_previous"},
        {"name": "transform"},
        {"name": "request_approval"},
        {"name": "write_excel"},
        {"name": "render_report"},
    ],
)

Step 2 — fetch_recent (MCP §16.5 step 3 — raw inbox first)

Recent window (today - days_back .. today).

workflow_runner.start_step(handle.run_id, 0,
                           project_slug=project_slug)
raw_recent = mcp__gsc__enhanced_search_analytics(
    siteUrl=project_config["gsc"]["site_url"],
    startDate=(today - days_back).isoformat(),
    endDate=today.isoformat(),
    dimensions=dimensions,    # default: ["page"]
)
inbox_recent = (
    workspace_root / "projects" / project_slug
    / "inbox" / "gsc"
    / f"{today.isoformat()}-enhanced_search_analytics-decay-recent-{project_slug}.json"
)
inbox_recent.parent.mkdir(parents=True, exist_ok=True)
inbox_recent.write_text(json.dumps(raw_recent, ensure_ascii=False, indent=2))
workflow_runner.finish_step(handle.run_id, 0,
                            project_slug=project_slug,
                            output_ref=str(inbox_recent))

Step 3 — fetch_previous (previous window for delta — MUST succeed)

mcp__gsc__enhanced_search_analytics covering the PREVIOUS window of equal length (today - 2*days_back .. today - days_back). Persist to inbox/gsc/{date}-enhanced_search_analytics-decay-previous-{slug}.json.

Both windows are required. Unlike gsc-pull (where previous-window failure is non-fatal first-run), decay analysis has no signal without the comparison baseline. Failure here triggers DURUR #1 (do NOT proceed with one-window data).

Step 4 — transform

Pure compute via scripts/discovery/content_decay_transform.py:

python3 scripts/discovery/content_decay_transform.py \
    --recent   inbox/gsc/{date}-enhanced_search_analytics-decay-recent-{slug}.json \
    --previous inbox/gsc/{date}-enhanced_search_analytics-decay-previous-{slug}.json \
    --output-dir _state/transform/{run_id}/

Produces a JSON array (content_decay) shaped to the master-excel schema. URL normalization (D-03) is applied here, not at fetch time, so the raw inbox copy is byte-faithful to the MCP response. The transform is idempotent: same inputs → byte-identical output. Sort: clicks_delta ascending (most decayed first), then url asc for tie-break determinism.

Step 4b — optional_dfs_cross_check (only when invoked)

When the optional mcp__dataforseo__dataforseo_labs_google_historical_rank_overview branch is active, first run the budget pre-flight via scripts/budget/check_budget.py against the project's 24h DFS credit total.

• Budget pre-flight PASS → fetch DFS historical rank, persist raw to inbox/dfs/{date}-historical_rank_overview-decay-{slug}.json, enrich action with a short note (e.g. "rank also dropped in DFS") for rows where the DFS series confirms the decay direction.
• Budget pre-flight FAIL → DURUR #7 (StopAndAwaitApproval). Do NOT silently fall back to GSC-only. The skill exits with awaiting_approval; the manager must explicitly authorize either raising the budget cap or skipping the cross-check (recorded as an ADR), then resume.

from scripts.budget import check_budget
budget_envelope = check_budget.preflight(
    project_config_path=project_root / "project.config.json",
    events_path=project_root / "_state" / "events.jsonl",
    estimated_credits=1,    # one DFS historical_rank_overview call
)
if budget_envelope["exceeded"]:
    workflow_runner.request_approval(
        handle.run_id, project_slug=project_slug,
        approver="user",
        subject="DFS historical_rank cross-check budget aşıldı; cap yükseltilsin mi?",
        step_index=3,
    )
    raise check_budget.BudgetGateError("DFS budget pre-flight failed; awaiting_approval")

Step 5 — request_approval (skill EXIT awaiting_approval)

workflow_runner.request_approval(
    handle.run_id, project_slug=project_slug,
    approver="user",
    subject=f"Content decay {len(rows)} URL hesaplandı, master.xlsx#content_decay'e yazalım mı?",
    step_index=3,
)
# Skill exits here. The user replies in a fresh session; resume below.

Step 6 — Resume (approve → continue)

workflow_runner.approve(handle.run_id, project_slug=project_slug,
                        approver="user")

Step 7 — write_excel (atomic, schema-validated)

Single idempotent committer.commit call for the content_decay sheet (replace — re-running refreshes the snapshot, never duplicates rows; routes through transaction.py: backup + lock + schema validation + provenance). Note: the transform module itself does NOT import the committer (scripts.orchestration.committer) — only the skill orchestrator layer does (cross-module IMPORT discipline).

from scripts.orchestration import committer
committer.commit(
    workbook_path=workspace_root/"projects"/project_slug/"master.xlsx",
    sheet="content_decay",
    rows=content_decay_rows,
    run_id=handle.run_id,
    project_slug=project_slug,
    writer="content-decay",
)

Step 8 — render_report

render_template.py templates/reports/content-decay.template.md data.json → outputs/reports/{date}-content-decay.md. Variables (all 13 the template references — render hard-fails on any missing): $project_slug, $date, $days_back, $run_id, $total_urls, $rows_written, $decay_count, $retired_count, $top_decay_url, $top_decay_delta, $trend_distribution, $pillar_summary, $report_summary.

Step 9 — Provenance event

One provenance entry per MCP call (two for GSC, plus one DFS when the optional branch fires).

from scripts.state import events_writer
events_writer.append_provenance(
    project_id=project_slug,
    source={"kind": "gsc_mcp", "mcp_server": "gsc",
            "mcp_tool": "gsc__enhanced_search_analytics",
            "response_bytes": len(json.dumps(raw_recent))},
    operation="project_excel",
    target_excel_sheet="content_decay",
    rows_written=len(content_decay_rows),
)
# Repeat for raw_previous (also gsc_mcp). When DFS branch ran:
# source.kind=dataforseo_mcp + cost.credits=1 + budget_key.

Step 10 — complete

workflow_runner.complete(handle.run_id, project_slug=project_slug, outputs={
    # F5: outputs.* must be STRING-TYPED.
    "content_decay_rows":      str(len(content_decay_rows)),
    "decay_count":             str(meta["trend_counts"]["DECAY"]),
    "retired_count":           str(meta["trend_counts"]["RETIRED"]),
    "report_path":             str(report_path),
    "raw_recent":              str(inbox_recent),
    "raw_previous":            str(inbox_previous),
})

URL normalization (D-03 invariant)

Every URL passing through this skill is normalized via scripts.discovery.content_decay_transform.normalize_url. The function is idempotent: normalize_url(normalize_url(u)) == normalize_url(u). Rules: lowercase scheme+host, IDN→punycode, strip default ports, strip trailing slash (root excluded), drop fragment, drop tracking params, sort remaining query keys.

The transform self-checks idempotency on every emitted URL — a drift between transform and downstream consumers is escalated as DURUR #3 rather than silently masked.

Period delta semantics

recent   window:  [today - days_back, today]            (default 90d)
previous window:  [today - 2*days_back, today - days_back]

Both windows must have equal length. The transform aggregates clicks + impressions + impression-weighted position per normalized URL across each window, then labels the trend per R-85 (single source — rules/content-update-discipline.md). The clicks delta_pct is still the emitted column; position/impressions feed the DECISION only (the 8-column schema is unchanged).

clicks_delta = clicks_recent - clicks_previous
delta_pct    = (clicks_recent - clicks_previous) / clicks_previous * 100,
               rounded 2dp; clamped to ±100 when previous=0
               (mirrors gsc-pull's _delta_pct, Phase 6 paterni)

trend  (R-85 multi-signal — see rules/content-update-discipline.md §R-85):
   NEW      if previous clicks=0 and recent>0
   RETIRED  if recent clicks=0  and previous>0
   GROWTH   if clicks delta_pct ≥ +20
   DECAY    if  (clicks Δ% < clicks_threshold  AND position worsened > position_threshold)
            OR  (impressions Δ% < -40%          AND ranking trend negative)
   STABLE   otherwise  ← a clicks-only drop with NO position/impression
                          corroboration is STABLE, not DECAY (single-signal
                          volatility ≠ decay — R-85 rationale)

profile-aware thresholds (clicks/position branch; impressions branch fixed):
   YMYL        : clicks_threshold -20%, position_threshold +3  (stricter)
   e-commerce  : -30% / +5
   other/default: -30% / +5
   (resolved via scripts/util/profile_aware_defaults.cascade_default — a
    project.config tuning key or an explicit override wins over the profile
    default; meta records the resolved thresholds + which R-85 branch fired.)

pillar  = first non-empty path segment (e.g. /blog/x → "blog")
action  = trend → deterministic prescription
            DECAY   → "investigate + refresh"
            STABLE  → "monitor"
            GROWTH  → "double-down"
            NEW     → "new content tracking"
            RETIRED → "redirect or revive review"

YoY mode (--yoy): compares the recent window against the same window one year earlier (the --previous payload is that year-ago window). When the year-ago data is present it is used as the decay baseline; when it is absent the transform refuses to fabricate verdicts — it emits a meta.yoy_unavailable=true note and zero rows (never fakes a YoY baseline).

DURUR conditions (9)

Stop and flag the manager — do not patch, do not fall back.

1. Either mcp__gsc__enhanced_search_analytics call (recent OR previous) returns auth/network/scope error. Decay analysis has no signal without both windows; STOP — do not proceed with one-window data.
2. Raw JSON inbox path cannot be created (workspace path missing or non-writable).
3. URL normalization output drifts (idempotency check fails inside content_decay_transform.transform).
4. master.xlsx#content_decay column count or names don't match schema (schemas/master-excel.schema.json#content_decay, 8 required_columns).
5. committer.commit raises RowSchemaError for content_decay.
6. workflow_runner.create_run fails schema validation.
7. Optional DFS historical_rank_overview invoked AND budget pre- flight FAILS → STOP, transition to awaiting_approval. Manager bilgilendirilir; do NOT silently fall back to GSC-only (false-success failure mode the brief explicitly forbids).
8. Both windows aggregate to zero rows (ContentDecayError: no data in window). Decay-specific: there is no signal to project.
9. Window dates overlap (caller logic error; recent.start ≤ previous.end). Decay-specific guard against silently double-counting. The skill orchestrator validates window arithmetic before fetch.

PSEO_WORKSPACE_ROOT env unset → also a STOP (inherited from workflow_runner / events_writer discipline; folded into DURUR #2's "workspace path missing" surface).

Cross-references

• Schemas: schemas/master-excel.schema.json (content_decay sheet, 8 required_columns at lines 173-180), schemas/events.schema.json (source.kind=gsc_mcp / dataforseo_mcp, target_excel_sheet=content_decay), schemas/cross-sheet-invariants.json (D-03 invariant), schemas/skill-frontmatter.schema.json (this frontmatter).
• Cross-modules (IMPORT-only): scripts/state/workflow_runner.py, scripts/excel/transaction.py, scripts/state/events_writer.py, scripts/reporting/render_template.py, scripts/budget/check_budget.py (optional DFS branch only — not for the GSC-only path).
• Transform: scripts/discovery/content_decay_transform.py (normalize_url, infer_pillar, transform, CONTENT_DECAY_COLUMNS, ContentDecayError).
• Tests: tests/skills/test_content_decay.py (≥6 cases incl. trend coverage, ±100 clamp, sort, schema column match, smoke E2E).
• Template: templates/reports/content-decay.template.md.

Discipline checklist

• TODO/fallback YASAK — every DURUR raises, none silently downgrade. The optional DFS branch's budget-fail path is awaiting_approval, not a silent GSC-only fallback.
• Schema-first — frontmatter validates against schemas/skill-frontmatter.schema.json Draft 7.
• Plugin-agnostik — no slug literals; project_slug flows through. 0-tolerance ADR-008 + D-010 Path B.
• ADR-013: Use when/Also use when/Do not use when are STRING content inside description, not separate fields.
• Cross-module IMPORT discipline — transaction / workflow_runner / events_writer / check_budget are imported, never modified from this skill. The transform module itself does NOT import scripts.excel.transaction (skill-orchestrator-only).
• F1: write target is master.xlsx (lowercase, schema-shaped).
• F5: outputs.* values are STRING-TYPED (artifact paths or stringified counts), never raw ints.
• Append-only state — events emitted via events_writer.append_provenance, one per MCP call; workflow run JSON only forward-flips step status.