MCPInstall

parallel-memory

Recall past Parallel Task, Monitor, and FindAll runs when they may help; evict runs or clear memory when asked.

Installs
2.3K
Last 24h
+26
Trending rank
#4794
Security
Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/parallel-web/parallel-agent-skills --skill parallel-memory
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads parallel-memory automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Parallel Memory

Action: $ARGUMENTS

Requires parallel-cli >=0.8.1. If the installed version is older, or parallel-cli memory --help fails with no such command or similar, tell the user to update parallel-cli, then retry.

When to use

  • Inspect memory only when prior Parallel work may help fulfill the request or the user asks to retrieve, evict, or clear it.
  • Memory results are excerpts from past runs; fetch the source run for full records, and launch a fresh run when current information is required.

Choose the operation

User intentOperation
Recall prior work about a topicRetrieve with a concise query
Show recent past runsRetrieve without query
Remove one saved Task, Monitor, or FindAll sourceEvict by exact kind and id
Permanently remove all entries from your personal MemoryClear memory
Turn memory offDirect the user to account settings; do not clear as a substitute

Use the CLI

Use parallel-cli memory for retrieve, evict, and clear operations.

  • If memory is not eligible, report the returned reason; it distinguishes rollout, organization settings, account opt-in, and key eligibility.
  • On a key-eligibility error, tell the user to reauthenticate.

Retrieve memory

Form a short semantic query that describes the prior work to find. Apply filters when they help. Empty results is a successful retrieval with no matches, not an error.

  • Set kind to task, monitor, or findall when it clearly narrows the retrieval.
  • Set since for an explicit timestamp boundary (RFC 3339, e.g. 2026-08-01T00:00:00Z).
  • Omit query when retrieving recent memories rather than a topic.

Retrieve by query:

parallel-cli memory retrieve \
  --query "serverless inference vendors"

For recent memories:

parallel-cli memory retrieve \
  --limit 5

Use results

Available fields vary by kind:

  • task: use id, updated_at, input_excerpt, and output_excerpt.

  • monitor: use the monitor id, status, query excerpt, and matching event IDs, timestamps, and excerpts.

  • findall: use id, updated_at, objective excerpt, and matched_count.

  • Fetch the original Task result, Monitor events, or FindAll result when exact output, entities, citations, or provenance matter.

  • Summarize the useful findings and unresolved questions.

  • Lead with what the prior work established, then list the contributing saved runs with kind, ID, and timestamp.

  • Distinguish recalled information from any fresh verification.

  • Parallel runs do not consult Memory. If recalled information may be useful, include the relevant details in the new run's input.

Expect ingestion to be asynchronous. Do not promise that a newly completed run will be immediately retrievable.

Evict or clear memory

Evict a single run from your personal Memory, or clear it entirely. These do not delete the underlying Parallel runs. Ask for confirmation before clearing unless the user already asked for it.

parallel-cli memory evict \
  --kind task \
  --id "trun_example"
parallel-cli memory clear \
  --confirm-clear

FAQ

What does the parallel-memory skill do?

Recall past Parallel Task, Monitor, and FindAll runs when they may help; evict runs or clear memory when asked.

How do I install parallel-memory?

Run npx skills add https://github.com/parallel-web/parallel-agent-skills --skill parallel-memory in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/parallel-memory/ (personal) or .claude/skills/parallel-memory/ (project).

Which AI agents can use parallel-memory?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is parallel-memory safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains parallel-memory?

It is published by parallel-web in parallel-web/parallel-agent-skills. It has 2,321 recorded installs.

More from parallel-web/parallel-agent-skills

View all →

parallel-deep-research

parallel-web/parallel-agent-skills

ONLY use when user explicitly says 'deep research', 'exhaustive', 'comprehensive report', or 'thorough investigation'. Slower and more expensive than parallel-web-search. For normal research/lookup requests, use parallel-web-search instead. Supports follow-ups with a known prior Task interaction ID.

OfficialProductivity & Automation15.7K installs

parallel-web-search

parallel-web/parallel-agent-skills

CLI-backed web search. Use when the user explicitly invokes this skill, needs CLI-only controls or saved JSON output, or no Parallel websearch MCP tool is available. When the bundled Parallel Search MCP is available, prefer its websearch tool for ordinary lookups and current-information queries. Only use parallel-deep-research if the user explicitly requests deep or exhaustive research.

OfficialProductivity & Automation14.5K installs

parallel-web-extract

parallel-web/parallel-agent-skills

CLI-backed URL extraction. Use when the user explicitly invokes this skill, needs CLI-only controls or saved JSON output, or no Parallel webfetch MCP tool is available. When the bundled Parallel Search MCP is available, prefer its webfetch tool for ordinary webpages, articles, PDFs, and JavaScript-heavy sites.

OfficialAI & Agents13.6K installs

parallel-data-enrichment

parallel-web/parallel-agent-skills

Bulk data enrichment. Adds web-sourced fields (CEO names, funding, contact info) to lists of companies, people, or products. Use for enriching CSV files or inline data. Supports multi-turn: pass --previous-interaction-id from a prior research task to carry context forward.

OfficialProductivity & Automation13.6K installs

status

parallel-web/parallel-agent-skills

Check running research task status by run ID

OfficialProductivity & Automation13.5K installs

result

parallel-web/parallel-agent-skills

Get completed research task result by run ID

OfficialProductivity & Automation13.4K installs

Popular ai & agents skills

View category →

google-agents-cli-publish

google/agents-cli

This skill should be used when the user wants to "publish an agent", "publish my ADK agent", "register an agent with Gemini", "publish to Gemini" (formerly Gemini Enterprise), or needs guidance on the agents-cli publish gemini command. Also use when the user wants to "manage agents in Agent Registry", "list/update/delete registered agents", or "register an MCP server". Covers ADK vs A2A registration modes, programmatic and interactive usage, flag reference, auto-detection from deployment metadata, Agent Registry fleet management, and troubleshooting. Part of the agents-cli skills suite. Do NOT use for deployment (use google-agents-cli-deploy).

AI & Agents513.9K installs

google-agents-cli-eval

google/agents-cli

This skill should be used when the user wants to "run an evaluation", "evaluate my agent", "evaluate my ADK agent", "write an eval dataset", "analyze eval failures", "compare eval results", "optimize agent", or needs guidance on the Gemini platform eval methodology and the Quality Flywheel. Covers eval metrics, dataset schema, LLM-as-judge scoring, and common failure causes. Applies to any agents-cli project, whatever framework the agent is written in. Do NOT use for agent API code patterns (ADK: use google-agents-cli-adk-code), deployment (use google-agents-cli-deploy), or project scaffolding (use google-agents-cli-scaffold).

AI & Agents513.5K installs

skill-creator

anthropics/skills

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

OfficialAI & Agents416.4K installs

codex-pet

prime-skills/runcomfy-agent-skills

Codex Pet generator on RunComfy. Build a Codex-compatible Codex Pet spritesheet.webp + pet.json from a single reference image, drop it into ${CODEXHOME:-$HOME/.codex}/pets/ / and Codex picks it up as a custom Codex Pet next to the 8 built-ins. This skill produces the exact Codex Pet atlas Codex expects (1536x1872 PNG/WebP, 8 cols x 9 rows, 192x208 cells, 9 animation states — idle, running-right, running-left, waving, jumping, failed, waiting, running, review). Calls OpenAI GPT Image 2 edit ONCE via the local RunComfy CLI as runcomfy run openai/gpt-image-2/edit to produce a canonical Codex Pet pose, then assembles all 9 animation rows programmatically with ImageMagick micro-transforms — no Codex Pro, no $imagegen, no OPENAIAPIKEY required, only RUNCOMFYTOKEN. Triggers on "codex pet", "create codex pet", "make codex pet", "hatch codex pet", "/hatch image", "desktop pet codex", "codex pets", "spritesheet.webp", or any explicit ask to build a custom pet for OpenAI Codex.

AI & Agents402.1K installs

full-output-enforcement

leonxlnx/taste-skill

Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.

AI & Agents401K installs

executing-plans

obra/superpowers

Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available

AI & Agents245.7K installs