Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/parallel-web/parallel-agent-skills/parallel-memorynpx skills add parallel-web/parallel-agent-skills --skill parallel-memorygit clone --depth 1 https://github.com/parallel-web/parallel-agent-skillsWhat 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 | $0.00028 | $0.00809 |
| Opus 5 | $0.00014 | $0.00404 |
| Sonnet 5 | $0.00006 | $0.00162 |
| Haiku 4.5 | $0.00003 | $0.00081 |
Grade A, and why
parallel-memory 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 2d 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Parallel Memory
Action: $ARGUMENTS
Requires
parallel-cli >=0.8.1. If the installed version is older, orparallel-cli memory --helpfails withno such commandor similar, tell the user to updateparallel-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 intent | Operation |
|---|---|
| Recall prior work about a topic | Retrieve with a concise query |
| Show recent past runs | Retrieve without query |
| Remove one saved Task, Monitor, or FindAll source | Evict by exact kind and id |
| Permanently remove all entries from your personal Memory | Clear memory |
| Turn memory off | Direct 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
kindtotask,monitor, orfindallwhen it clearly narrows the retrieval. - Set
sincefor an explicit timestamp boundary (RFC 3339, e.g.2026-08-01T00:00:00Z). - Omit
querywhen 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: useid,updated_at,input_excerpt, andoutput_excerpt.monitor: use the monitorid, status, query excerpt, and matching event IDs, timestamps, and excerpts.findall: useid,updated_at, objective excerpt, andmatched_count.
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.
- 2d ago First seen · 92 lines · 28 tokens per session scan A 0199db203ee4
parallel-memory is a skill published in the GitHub repository parallel-web/parallel-agent-skills (73 stars, last pushed 18d ago), licensed MIT. It adds 28 tokens to every session and 809 once invoked, about $0.0001 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.
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