Gestion de mémoire pour campagnes SEO/GEO

VérifiéSûr

Système de mémoire en trois niveaux pour persister le contexte des campagnes SEO/GEO entre sessions Claude, avec gestion automatique des données chaudes, tièdes et froides.

Spar Skills Guide Bot
ProductiviteAvancé
05/09/2026
Claude Code
#memory-management#seo-geo#context-persistence#session-hooks#knowledge-base

Recommandé pour

Synthèse automatique

Gère un système de mémoire à trois niveaux HOT/WARM/COLD pour conserver le contexte et les décisions d’une campagne SEO/GEO d’une session Claude Code à l’autre.

Points forts

  • Met en place des hooks SessionStart/Stop/PostToolUse pour charger le contexte chaud et rappeler les boucles ouvertes obsolètes.
  • Définit des règles explicites de promotion et de rétrogradation selon le nombre de références et l’ancienneté.
  • Agrège l’état du projet entre les compétences et tient un index wiki avec détection des contradictions et des pages orphelines.
  • Sépare un cache chaud durable, des constats WARM datés et une archive COLD pour gérer le cycle de vie.

Limites

  • Dépend des hooks Claude Code et du contrat de compétence/modèle d’état de cette bibliothèque, donc peu portable tel quel vers d’autres environnements d’agents.
  • La mémoire HOT est limitée à 80 lignes et les pages wiki compilées nécessitent une confirmation explicite de l’utilisateur avant écriture.
  • Certaines fonctions de maintenance (wiki-lint, aperçu de retrait) relèvent des phases 2/3 et peuvent seulement prévisualiser l’archivage sans l’exécuter.
Quand l'utiliser

À utiliser lorsque les décisions, mots-clés, concurrents ou points ouverts d’un projet SEO/GEO doivent survivre entre les sessions ou être retrouvés plus tard.

Quand l'éviter

À éviter pour des tâches ponctuelles, des environnements d’agents non Claude, ou lorsque vous ne souhaitez pas conserver le contexte du projet dans des fichiers de mémoire.

Analyse de sécurité

Sûr
Score qualité86/100

The skill only manages project memory files and directories (hot cache, warm storage, archive, wiki index) within a local repository. It does not declare or invoke shell commands, network requests, credential handling, or destructive system operations. The instruction to delete memory/wiki/ is limited to a derived artifact directory and is reversible/regenerable.

Aucun point d'attention détecté

Comment cette analyse est faite

Exemples

Save campaign context
Remember that our primary keyword is “AI SEO tools,” our top competitor is Surfer, and the next milestone is a technical audit due Friday. Save this to the project memory.
Recall project status
What do we know about the decisions and open loops from last week’s SEO audit? Check project memory and summarize the current status.
Set up memory for a new project
Set up the HOT/WARM/COLD memory structure for a new SEO/GEO project for example.com and show me the initial hot cache and open loops.

name: memory-management description: Persist SEO/GEO campaign context across Claude sessions with automatic hot-list, active work, and archive tiers. 项目记忆/跨会话 Use when this capability is needed. metadata: author: aaron-he-zhu

Memory Management

SEO & GEO Skills Library · 20 skills for SEO + GEO · ClawHub · skills.sh System Mode: This cross-cutting skill is part of the protocol layer and follows the shared Skill Contract and State Model.

This skill implements a three-tier memory system (HOT/WARM/COLD) for SEO and GEO projects. HOT memory (80 lines max) loads automatically every session via the SessionStart hook. WARM memory loads on demand per skill. COLD memory is archived data queried only when explicitly requested. The skill manages the full lifecycle: capture, promote, demote, and archive.

System role: Campaign Memory Loop. It defines how project context is captured, promoted, archived, and handed off across sessions. It is the sole executor of WARM-to-COLD archival and the aggregator for cross-skill project status queries.

When This Must Trigger

Use this whenever project state should survive the current session — even if the user doesn't use memory terminology:

  • User says "remember this", "save this", "keep track of this"
  • User asks "what did we decide", "what do we know", "project status"
  • Setting up memory structure for a new SEO project
  • After completing audits, ranking checks, or performance reports (Stop hook reminds automatically)
  • When project context needs updating (new keywords, competitors, priorities)
  • When you need to look up historical data or project-specific terminology
  • After 30+ days of work to clean up and archive stale data
  • When open-loops.md has items older than 7 days (SessionStart hook reminds automatically)

What This Skill Does

  1. HOT Cache Management: Maintains memory/hot-cache.md (80 lines max) — loaded automatically every session by SessionStart hook
  2. WARM Storage: Organizes dated findings in memory/ subdirectories — loaded on demand by relevant skills
  3. COLD Archive: Moves stale data (90+ days unreferenced) to memory/archive/ with date prefix
  4. Promotion: Elevates frequently-referenced findings from WARM to HOT (3+ refs in 7 days, or 2+ skill refs)
  5. Demotion: Moves unreferenced HOT items to WARM (30 days), WARM to COLD (90 days)
  6. Cross-Skill Aggregation: When user asks "what do we know", aggregates from all memory/ subdirectories
  7. Open Loop Tracking: Maintains memory/open-loops.md, reminds user of stale items via SessionStart hook
  8. Wiki Index Maintenance: Compiles memory/wiki/index.md — a structured, auto-refreshed index of all WARM files with precise fields (score, 健康度, status, next_action, mtime) and best-effort summaries. Supports project isolation via memory/wiki/<project>/index.md. Auto-refreshed on PostToolUse; user confirmation not required (index is a fully rebuildable derived artifact). Delete memory/wiki/ at any time to revert to pre-wiki behavior.
  9. Wiki Compiled Pages (Phase 2): Generates interlinked entity, keyword, and topic pages from WARM files with source hash tracking, contradiction detection, and confidence-labeled reconciliation. Requires user confirmation before writing.
  10. Wiki Lint (Phase 2): Detects contradictions, orphan pages, stale claims, missing pages, and source hash mismatches across wiki and WARM files via /seo:wiki-lint.
  11. WARM Retirement Preview (Phase 3): wiki-lint --retire-preview lists WARM files fully covered by wiki compiled pages as retirement candidates. Actual archival to COLD requires explicit user confirmation.

Quick Start

Start with one of these prompts. Finish with a hot-cache update plan and a handoff summary using the repository format in Skill Contract.

Initialize Wiki Index

Refresh wiki index
Build wiki index for [project name]

Generates memory/wiki/index.md from existing WARM files. Required once to enable wiki features; subsequent refreshes happen automatically.

Initialize Memory Structure

Set up SEO memory for [project name]
Initialize memory structure for a new [industry] website optimization project

Update After Analysis

Update memory after ranking check for [keyword group]
Refresh hot cache with latest competitor analysis findings

Query Stored Context

What are our hero keywords?
Show me the last ranking update date for [keyword category]
Look up our primary competitors and their domain authority

Promotion and Demotion

Promote [keyword] to hot cache
Archive stale data that hasn't been referenced in 30+ days

Glossary Management

Add [term] to project glossary: [definition]
What does [internal jargon] mean in this project?

Skill Contract

Expected output: a memory update plan, hot-cache changes, and a short handoff summary.

  • Reads: current campaign facts, new findings from other skills, approved decisions, and the shared State Model.
  • Writes: updates to memory/hot-cache.md, memory/open-loops.md, memory/decisions.md, and related memory/ folders. Manages WARM-to-COLD archival in memory/archive/. Compiles memory/wiki/index.md (auto-refreshed) and wiki compiled pages (user-confirmed).
  • Promotes: durable strategy, blockers, terminology, entity candidates, and major deltas. Applies temperature lifecycle rules: promote to HOT on high reference frequency, demote on staleness.
  • Next handoff: use the Next Best Skill below when the project memory baseline is ready for active work.

Temperature Lifecycle Rules

See references/promotion-demotion-rules.md for the full promotion/demotion table and action procedures.

Hook Integration

This skill's behavior is reinforced by the library's prompt-based hooks:

  • SessionStart: loads memory/hot-cache.md, reminds of stale open loops; loads memory/wiki/<project>/index.md (or global index.md) if it exists; provides light-user guidance based on Quick Status when next_action items are available
  • PostToolUse: after any WARM file write, silently refreshes memory/wiki/index.md (Phase 1); prompts to update compiled pages (Phase 2)
  • Stop: prompts to save session findings, auto-saves veto issues to hot-cache; appends changelog entry to index.md bottom

Data Sources

See CONNECTORS.md for tool category placeholders.

With ~~SEO tool + ~~analytics + ~~search console connected: Automatically populate memory from historical data: keyword rankings over time, competitor domain authority changes, traffic metrics, conversion data, backlink profile evolution. The skill will fetch current rankings, alert on significant changes, and update both hot cache and cold storage.

With manual data only: Ask the user to provide:

  1. Current target keywords with priority levels
  2. Primary competitors (3-5 domains)
  3. Key performance metrics and last update date
  4. Active campaigns and their status
  5. Any project-specific terminology or abbreviations

Proceed with memory structure creation using provided data. Note in CLAUDE.md which data requires manual updates vs. automated refresh.

Instructions

When a user requests SEO memory management:

1. Initialize Memory Structure

For new projects, create the directory structure defined in the State Model. Key directories: memory/ (decisions, open-loops, glossary, entities, research, content, audits, monitoring) plus memory/wiki/ (auto-managed compiled index with optional per-project subdirectories).

Templates: hot-cache-template.md · glossary-template.md · Wiki spec

2. Context Lookup Flow

When a user references something unclear, follow this lookup sequence:

Step 1: Check CLAUDE.md (Hot Cache)

  • Is it in active keywords?
  • Is it in primary competitors?
  • Is it in current priorities or campaigns?

Step 2: Check Wiki Index (memory/wiki/index.md or project-level) — locate relevant WARM files

Step 3: Check memory/glossary.md

  • Is it defined as project terminology?
  • Is it a custom segment or shorthand?

Step 4: Check Cold Storage

  • Search memory/research/keywords/ for historical keyword context
  • Search memory/research/competitors/ for past analyses
  • Search memory/monitoring/reports/ for archived mentions

Step 5: Ask User

  • If not found in any layer, ask for clarification
  • Log the new term in glossary if it's project-specific

Example lookup:

User: "Update rankings for our hero KWs"

Step 1: Check CLAUDE.md → Found "Hero Keywords (Priority 1)" section
Step 2: Extract keyword list from hot cache
Step 3: Execute ranking check
Step 4: Update both CLAUDE.md and memory/monitoring/rank-history/YYYY-MM-DD-ranks.csv

3. Promotion & Demotion Logic

Reference: See references/promotion-demotion-rules.md for detailed promotion/demotion triggers (keywords, competitors, metrics, campaigns) and the action procedures for each.

4. Update Triggers, Archive Management & Cross-Skill Integration

Reference: See references/update-triggers-integration.md for the complete update procedures after ranking checks, competitor analyses, audits, and reports; monthly/quarterly archive routines; and integration points with all 8 connected skills (keyword-research, rank-tracker, competitor-analysis, content-gap-analysis, seo-content-writer, content-quality-auditor, domain-authority-auditor).

5. Memory Hygiene Checks

When invoked for review or cleanup:

  1. Line count check: Count lines in memory/hot-cache.md. If >80, list oldest entries for archival.
  2. Byte check: If hot-cache exceeds 25KB, warn and recommend trimming long entries.
  3. Staleness scan: List memory files older than 30 days that have not been referenced. Recommend archival for files >90 days.
  4. Frontmatter audit: Check that all memory files (except hot-cache.md) have name, description, and type in their frontmatter. Report any missing fields.

6. Save Results

After delivering any memory update or aggregation to the user, ask:

"Save these results for future sessions?"

If yes, write a dated summary to the appropriate memory/ path using filename YYYY-MM-DD-<topic>.md containing:

  • One-line verdict or headline finding
  • Top 3-5 actionable items
  • Open loops or blockers
  • Source data references

If any veto-level issue was found (CORE-EEAT T04, C01, R10 or CITE T03, T05, T09), also append a one-liner to memory/hot-cache.md without asking.

Validation Checkpoints

Structure Validation

  • [ ] memory/hot-cache.md exists and is under 80 lines
  • [ ] memory/ directory structure matches the shared state model
  • [ ] glossary.md exists and is populated with project basics
  • [ ] All historical data files include timestamps in filename or metadata

Content Validation

  • [ ] CLAUDE.md "Last Updated" date is current
  • [ ] Every keyword in hot cache has current rank, target rank, and status
  • [ ] Every competitor has domain authority and position assessment
  • [ ] Every active campaign has status percentage and expected completion date
  • [ ] Key Metrics Snapshot shows "Previous" values for comparison

Lookup Validation

  • [ ] Test lookup flow: reference a term → verify it finds it in correct layer
  • [ ] Test promotion: manually promote item → verify it appears in CLAUDE.md
  • [ ] Test demotion: manually archive item → verify removed from CLAUDE.md
  • [ ] Glossary contains all custom segments and shorthand used in CLAUDE.md

Update Validation

  • [ ] After ranking check, memory/monitoring/rank-history/ has a dated snapshot or export
  • [ ] After competitor analysis, memory/research/competitors/ has a dated file
  • [ ] After audit, top action items appear in CLAUDE.md priorities
  • [ ] After monthly report, metrics snapshot reflects new data

Examples

Reference: See references/examples.md for three complete examples: (1) updating hero keyword rankings with memory refresh, (2) glossary lookup flow, and (3) initializing memory for a new e-commerce project.

Advanced Features

  • Smart Context Loading: Load full context for [campaign name] — retrieves hot cache + all cold storage files for a campaign
  • Memory Health Check: Run memory health check — finds orphaned files, missing timestamps, stale items, broken references
  • Bulk Promotion/Demotion: Promote all keywords ranking in top 10 to hot cache / Demote all completed campaigns from Q3
  • Memory Snapshot: Create memory snapshot for [date/milestone] — point-in-time copy for major milestones
  • Cross-Project Memory: Compare memory with [other project] — keyword overlaps, competitor intersections across projects
  • Wiki Lint: /seo:wiki-lint [--fix] [--project name] [--retire-preview] — contradictions, orphans, stale claims, hash mismatches. See commands/wiki-lint.md

Practical Limitations

  • Concurrent access: Use timestamped filenames to avoid overwrites from parallel sessions.
  • Cold storage retrieval: WARM/COLD files only load on demand. Hot cache is the primary cross-session mechanism.
  • Data freshness: Stale data (>90 days) should be flagged for refresh. Wiki index mtime field helps detect staleness.
  • Wiki compilation: Index is best-effort for summaries; precise fields (score, status, mtime) are deterministic. Delete memory/wiki/ anytime to revert.

Reference Materials

Next Best Skill

  • Primary: keyword-research — seed or refresh campaign strategy with current demand signals.

Converted and distributed by TomeVault — claim your Tome and manage your conversions.

<!-- tomevault:4.0:skill_md:2026-04-11 -->

Du fichier au premier essai

Le téléchargement contient exactement le contenu affiché sur cette fiche. Cette copie peut différer de la dernière version du dépôt source.

Consulter la source et ses fichiers annexes

Ce téléchargement contient uniquement SKILL.md. Les scripts, références, modèles et dépendances éventuels ne sont pas inclus. Récupérez les fichiers nécessaires depuis la source en conservant leur arborescence avant de poursuivre.

1. Télécharger le fichier

Télécharger SKILL.md

Depuis la racine d’un projet de test, enregistrez le fichier sous .skill-downloads/memory-management-for-seo-geo-campaigns-mtnxbs23/SKILL.md, ou utilisez la commande suivante. Ce dossier sert à examiner la skill avant son installation.

Commande pour macOS/Linux ou WSL : un shell POSIX et curl sont nécessaires. Sous Windows sans WSL, utilisez le bouton de téléchargement et créez le dossier manuellement.

mkdir -p '.skill-downloads/memory-management-for-seo-geo-campaigns-mtnxbs23' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/memory-management-for-seo-geo-campaigns-mtnxbs23/download' --output '.skill-downloads/memory-management-for-seo-geo-campaigns-mtnxbs23/SKILL.md.part' && mv '.skill-downloads/memory-management-for-seo-geo-campaigns-mtnxbs23/SKILL.md.part' '.skill-downloads/memory-management-for-seo-geo-campaigns-mtnxbs23/SKILL.md'

2. Vérifier les prérequis

Lisez SKILL.md avant de l’utiliser. Si le fichier cite des scripts ou services externes, examinez-les et préparez les accès nécessaires dans votre environnement de test.

Aucune section de prérequis reconnue dans ce fichier. Cela ne signifie pas qu’il est autonome : les bibliothèques, outils et accès peuvent être cités ailleurs dans le contenu ou dans le dépôt source.

Les plateformes de la fiche sont des indications du catalogue. Les chemins ci-dessous suivent la documentation des outils ; ils ne prouvent pas que cette skill y a été exécutée. Aucune version minimale de ces outils n’est attestée pour cette fiche.

3. Charger la skill

Après vérification, copiez le dossier complet dans le projet avec l’une des commandes ci-dessous, puis ouvrez une nouvelle session de l’outil. La commande s’arrête si un dossier du même nom existe déjà : comparez les fichiers avant de le remplacer.

Claude Code
test -f '.skill-downloads/memory-management-for-seo-geo-campaigns-mtnxbs23/SKILL.md' && test -s '.skill-downloads/memory-management-for-seo-geo-campaigns-mtnxbs23/SKILL.md' && mkdir -p '.claude/skills' && test ! -e '.claude/skills/memory-management' && cp -R '.skill-downloads/memory-management-for-seo-geo-campaigns-mtnxbs23' '.claude/skills/memory-management'

OpenSkills

OpenSkills doit déjà être installé. La procédure locale install/read est contrôlée avec OpenSkills 1.5.0, qui exige Node.js ≥ 20.6.0. Aucun slug du catalogue n’est résolu automatiquement.

Installation officielle d’OpenSkills
openskills install './.skill-downloads/memory-management-for-seo-geo-campaigns-mtnxbs23'

openskills read 'memory-management-for-seo-geo-campaigns-mtnxbs23'

La lecture doit afficher le contenu du fichier installé et son dossier de base. Elle ne lance ni la skill ni ses dépendances.

Pour un agent qui lit AGENTS.md, synchronisez ensuite l’index. Cette commande modifie AGENTS.md : relisez le diff avant de l’utiliser.

openskills sync

Mode manuel ou autre outil : joignez SKILL.md à une conversation, ou ouvrez-le dans un agent capable de lire les fichiers. Ajoutez les ressources annexes nécessaires. Il n’existe pas de dossier universel reconnu par tous les outils.

4. Faire un premier essai

Utilisez une entrée courte et fictive : un endpoint d’API, un petit document ou un brief d’interface. Dans une nouvelle conversation, joignez le fichier ou donnez son chemin à l’agent, puis adaptez cette demande :

Lis .skill-downloads/memory-management-for-seo-geo-campaigns-mtnxbs23/SKILL.md et applique ses instructions à cet exemple : [décrire une entrée de test]. Indique les fichiers, dépendances ou accès qui manquent. Produis le résultat demandé par la skill sans inventer de données ni exécuter de script non examiné.

Résultat attendu : une sortie correspondant aux instructions de la skill, ou une liste précise des prérequis manquants. Une simple confirmation de lecture ne valide pas le premier usage. Si une ressource externe est indisponible, ce parcours reste à tester.

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