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Workspace Memory Skill

skill-fightzy-simple-skills-workspace-memory-skill · by fightZy

Use when the task involves creating, maintaining, or querying repo-local workspace memory for a project. This skill organizes team-shared agent memory as Markdown files under the current workspace, captures session summaries, maintains layered memory indexes, crystallizes durable team conventions and design rationale, and retrieves memory progressively to reduce context and token cost.

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Install

$ agentstack add skill-fightzy-simple-skills-workspace-memory-skill

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Security review

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No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

Workspace Memory Skill

Overview

This skill manages project memory inside the current workspace as Markdown files. It is for small-team workflows where agents and developers need shared, durable context without turning the repo into an unstructured dump of transcripts.

Prefer script-generated metadata. The agent should focus on semantic inputs and body content, not on hand-writing frontmatter.

Read [references/layout.md](references/layout.md) for the memory tree. Read [references/templates.md](references/templates.md) for schema and body-template navigation. Read [references/config.md](references/config.md) for memory-language configuration.

Routing

Pick the narrowest operation that matches the request:

  • Initialize workspace memory:

Read [references/operations/initialize-memory.md](references/operations/initialize-memory.md)

  • Record a new session:

Read [references/operations/session-capture.md](references/operations/session-capture.md)

  • Compress recent memory into archive:

Read [references/operations/refine-recent.md](references/operations/refine-recent.md)

  • Query existing memory:

Read [references/operations/query-memory.md](references/operations/query-memory.md)

  • Maintain or deduplicate memory:

Read [references/maintenance.md](references/maintenance.md)

  • Extract durable knowledge:

Read [references/operations/crystal-maintenance.md](references/operations/crystal-maintenance.md)

  • Maintain topic summaries:

Read [references/operations/topic-summary-maintenance.md](references/operations/topic-summary-maintenance.md)

Core Rules

  • Keep memory repo-local and Markdown-first.
  • Treat structured metadata as system-owned fields. Generate or update them through scripts whenever possible.
  • Treat body sections as content-owned fields. The agent should focus on the actual summary, rationale, decisions, and follow-ups.
  • Prefer updating existing files over creating near-duplicates.
  • Do not invent unsupported scripts. If an operation card says the flow is currently manual, follow the manual flow.
  • Use script --help output as the final parameter contract when there is any ambiguity.
  • Read docs/memory/config.toml before authoring body content when the memory tree exists.
  • Keep filenames ASCII and keep memory headings in their scripted English form.
  • Write body prose in the configured content_language. If the config is missing, default to English.

Current Automation Boundary

Script-supported today:

  • initialization via scripts/init_memory.py
  • session capture via scripts/record_session.py
  • recent-to-archive compression via scripts/refine_memory.py
  • query retrieval via scripts/query_memory.py
  • crystal creation via scripts/create_crystal.py
  • crystal updates via scripts/update_crystal.py
  • topic-summary creation via scripts/create_topic_summary.py
  • topic-summary updates via scripts/update_topic_summary.py
  • language-policy validation via scripts/check_memory_language.py

Manual or partial today:

  • broader maintenance and deduplication flows are still reference-driven
  • broader derived-file freshness beyond recent/archive is still partial

Expected Outputs

Common outputs for this skill are:

  • a new or updated memory directory under the current workspace
  • one or more session files with script-generated metadata
  • updated recent or archived summaries
  • updated crystal or topic-summary files when the task requires durable knowledge extraction

Use file paths in your response when you create or update memory files.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.