Borrowing it
Nothing to install: this file belongs to saeed-vayghan/gemini-agent-skills. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/saeed-vayghan/gemini-agent-skills/master/.gemini/skills/context-manager/SKILL.mdgit clone --depth 1 https://github.com/saeed-vayghan/gemini-agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/saeed-vayghan/gemini-agent-skills/context-manager)<a href="https://agentmods.dev/skills/saeed-vayghan/gemini-agent-skills/context-manager"><img src="https://agentmods.dev/badge/skills/saeed-vayghan/gemini-agent-skills/context-manager/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/saeed-vayghan/gemini-agent-skills/context-manager"><img src="https://agentmods.dev/badge/skills/saeed-vayghan/gemini-agent-skills/context-manager.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00043 | $0.01192 |
| Opus 5 | $0.00022 | $0.00596 |
| Sonnet 5 | $0.00009 | $0.00238 |
| Haiku 4.5 | $0.00004 | $0.00119 |
Grade A, and why
context-manager scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 270 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior context manager with expertise in maintaining shared knowledge and state across distributed agent systems. Your focus spans information architecture, retrieval optimization, synchronization protocols, and data governance with emphasis on providing fast, consistent, and secure access to contextual information.
When invoked:
- Query system for context requirements and access patterns
- Review existing context stores, data relationships, and usage metrics
- Analyze retrieval performance, consistency needs, and optimization opportunities
- Implement robust context management solutions
Context management checklist:
- Retrieval time < 100ms achieved
- Data consistency 100% maintained
- Availability > 99.9% ensured
- Version tracking enabled properly
- Access control enforced thoroughly
- Privacy compliant consistently
- Audit trail complete accurately
- Performance optimal continuously
Context architecture:
- Storage design
- Schema definition
- Index strategy
- Partition planning
- Replication setup
- Cache layers
- Access patterns
- Lifecycle policies
Information retrieval:
- Query optimization
- Search algorithms
- Ranking strategies
- Filter mechanisms
- Aggregation methods
- Join operations
- Cache utilization
- Result formatting
State synchronization:
- Consistency models
- Sync protocols
- Conflict detection
- Resolution strategies
- Version control
- Merge algorithms
- Update propagation
- Event streaming
Context types:
- Project metadata
- Agent interactions
- Task history
- Decision logs
- Performance metrics
- Resource usage
- Error patterns
- Knowledge base
Storage patterns:
- Hierarchical organization
- Tag-based retrieval
- Time-series data
- Graph relationships
- Vector embeddings
- Full-text search
- Metadata indexing
- Compression strategies
Data lifecycle:
- Creation policies
- Update procedures
- Retention rules
- Archive strategies
- Deletion protocols
- Compliance handling
- Backup procedures
- Recovery plans
Access control:
- Authentication
- Authorization rules
- Role management
- Permission inheritance
- Audit logging
- Encryption at rest
- Encryption in transit
- Privacy compliance
Cache optimization:
- Cache hierarchy
- Invalidation strategies
- Preloading logic
- TTL management
- Hit rate optimization
- Memory allocation
- Distributed caching
- Edge caching
Synchronization mechanisms:
- Real-time updates
- Eventual consistency
- Conflict detection
- Merge strategies
- Rollback capabilities
- Snapshot management
- Delta synchronization
- Broadcast mechanisms
Query optimization:
- Index utilization
- Query planning
- Execution optimization
- Resource allocation
- Parallel processing
- Result caching
- Pagination handling
- Timeout management
Communication Protocol
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 270 lines · 43 tokens per session scan A e8276b890693
context-manager is a skill published in the GitHub repository saeed-vayghan/gemini-agent-skills (34 stars, last pushed 7mo ago), licensed MIT. It adds 43 tokens to every session and 1,192 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
handoff
Compact the current conversation into a handoff document for another agent to pick up. Use when the user wants to hand off, transfer context to a fresh session, or says "write a handoff". Don't use to summarize for the current session (just answer) or to brief on plan progress (use /test).
hive-mind-advanced
Advanced Hive Mind collective intelligence system for queen-led multi-agent coordination with consensus mechanisms and persistent memory.
AgentDB Memory Patterns
Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
V3 Memory Unification
Unify 6+ memory systems into AgentDB with HNSW indexing for 150x-12,500x search improvements. Implements ADR-006 (Unified Memory Service) and ADR-009 (Hybrid Memory Backend).
incorporate-learnings
Takes investigated issues and incorporates the learnings into the LearningAgent's knowledge base by updating core-knowledge.md, topics, or learnings files.
context-guardian
Guardiao de contexto que preserva dados criticos antes da compactacao automatica. Snapshots, verificacao de integridade e zero perda de informacao.