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 skills add Parcha-ai/parcha-skills --skill recallgit clone --depth 1 https://github.com/Parcha-ai/parcha-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/parcha-ai/parcha-skills/recall)<a href="https://agentmods.dev/skills/parcha-ai/parcha-skills/recall"><img src="https://agentmods.dev/badge/skills/parcha-ai/parcha-skills/recall/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/parcha-ai/parcha-skills/recall"><img src="https://agentmods.dev/badge/skills/parcha-ai/parcha-skills/recall.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 41 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
- medium Rogue Agent · line 41 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
- medium Rogue Agent · line 130 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00140 | $0.02493 |
| Opus 5 | $0.00070 | $0.01247 |
| Sonnet 5 | $0.00028 | $0.00499 |
| Haiku 4.5 | $0.00014 | $0.00249 |
Grade A, and why
recall 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 11d 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 — 217 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/recall: session memory engine
Claude Code and Codex sessions on this machine are indexed into a local SQLite engine. Query the index and read only the best-supported session instead of searching entire transcripts. All commands go through one CLI:
python3 scripts/recall.py <command> # relative to this skill directory
If Recall MCP tools are available in the current agent, immediately
read references/central-brain.md
before running commands and use those tools directly. Do not run the local CLI
as a parallel or fallback retrieval path. The same central instructions apply
when RECALL_URL is set, RECALL_MODE is remote or shadow, or
~/.config/recall-brain/client.json exists. Otherwise everything below is fully local and nothing
touches a network.
No index yet? Search anyway
If search reports the index does not exist (or doctor shows
db exists=False), search the raw JSONL transcripts immediately while the
first index builds:
rg -l -i "<terms>" ~/.claude/projects ~/.codex/sessions # candidate files
ls -t <hits> # newest first
rg -n -i -C3 "<terms>" <best-hit> # read the window
Choose terms and regular expressions based on the request. Exact identifiers
are stronger evidence than general prose. If rg is unavailable, use
grep -rl. Start the index in the background at the same time:
setsid nohup python3 scripts/recall.py index >/dev/null 2>&1 &
The first build over a large history can take many minutes; later runs are
incremental and fast. Tell the user when an answer came from a cold scan of the
raw transcripts. Once doctor shows a healthy db, switch to indexed search,
which ranks results, explains the WHY for each match, and matches identifiers
exactly.
First: pick the outcome
- Find / verify: answer "did we…", "which session…", "how did we…". Search, read the best hit's relevant window, answer with the session path as the receipt.
- Continue: resume in-progress work. This needs the session's tail plus its branch and worktree.
- Repeat: redo the same kind of task with fresh inputs. This needs the original driving prompts, verbatim.
- Skill-ify: turn the recipe into a reusable skill. This needs the steps that
worked, minus one-off data. Chain into the harness's skill creator when one
is installed; otherwise write the standard
SKILL.mdpackage directly.
What ships with it
5 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.
- 11d ago First seen · 217 lines · 140 tokens per session scan A d3c0acebd0d3
recall is a skill published in the GitHub repository Parcha-ai/parcha-skills (59 stars, last pushed today), licensed MIT. It adds 140 tokens to every session and 2,493 once invoked, about $0.0007 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
media-ingest
Ingest video, audio, PDF, book, screenshot, and GitHub repo content into the brain. Multi-format handling with entity extraction and backlink propagation. Covers video-ingest, youtube-ingest, and book-ingest subtypes.
mem0-oss-to-platform
Plan and then execute a migration of a project from the mem0 open-source / self-hosted SDK (the local Memory class) to the mem0 Platform / hosted / managed SDK (the MemoryClient class). Use this whenever a developer wants to move, switch, or migrate their mem0 usage off OSS/self-hosted to the hosted API — e.g.…
Cortex
Operate Cortex, the LifeOS memory system — the typed Knowledge Archive (People, Companies, Ideas, Research with typed related: links) plus recall of prior work sessions, ISAs, and conversations. Search, add, harvest, develop, ingest, distill, graph-navigate, recall. USE WHEN cortex, knowledge, knowledge base, search…
memory
Use when the user asks to remember, recall, forget, update, search, or inspect durable OpenSquilla memory, including profile facts in USER.md and long-term notes in MEMORY.md or memory//.md.
ha-data-stores
Map of Hope Agent's local data stores and safe read-only query workflow. Use when the user asks where Hope Agent stores data, wants to inspect sessions/messages/memory/logs/background jobs/knowledge indexes/settings, asks the model to query local app data, or debugging requires checking persisted state. Trigger…
establishing-project-context
Use when the user asks to establish shared project language, or project work exposes a conflicting, renamed, or deprecated domain term that needs active semantic modeling. Routine small tasks stay on the fast path.