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 RashadAnsari/myagents --skill forgetgit clone --depth 1 https://github.com/RashadAnsari/myagentsWrote 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/rashadansari/myagents/forget)<a href="https://agentmods.dev/skills/rashadansari/myagents/forget"><img src="https://agentmods.dev/badge/skills/rashadansari/myagents/forget/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/rashadansari/myagents/forget"><img src="https://agentmods.dev/badge/skills/rashadansari/myagents/forget.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 | $0.00012 | $0.00611 |
| Opus 5.5 | $0.00005 | $0.00244 |
| Sonnet 5.5 | $0.00002 | $0.00122 |
| Haiku 4.5 | $0.00001 | $0.00061 |
Grade A, and why
forget 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 5d 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 — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Task
Search agent memory and forget every entry that matches.
Subject: $ARGUMENTS
If the line above still shows a placeholder instead of a value, this platform does not pass arguments to skills: take the value from the user's message instead, and treat it as empty when the message gives none. Read every later mention of the placeholder as that value.
Step 1: Validate input
If $ARGUMENTS is empty or missing, stop immediately and tell the user:
Usage: /forget <what to forget>
Example: /forget my preference for two-space indentation
Example: /forget the Prisma migration workflow
Step 2: Get the project root
Run:
git rev-parse --show-toplevel
Store as PROJECT_ROOT.
Step 3: Search both memory stores in parallel
Run both at the same time:
project_search(agent-memory MCP server) withproject_root: PROJECT_ROOT,query: $ARGUMENTS,k: 10user_search(agent-memory MCP server) withquery: $ARGUMENTS,k: 10
After results arrive, filter each list: keep only entries whose content is meaningfully related to $ARGUMENTS. Discard unrelated results that surfaced only because of distant semantic similarity.
Store the filtered results as PROJECT_MATCHES and USER_MATCHES.
Step 4: Handle no matches
If both lists are empty after filtering, stop and tell the user:
No memory found matching: <$ARGUMENTS>
Step 5: Forget all matches
Immediately forget every entry in PROJECT_MATCHES and USER_MATCHES without asking for confirmation.
For each project memory, call project_forget (agent-memory MCP server) with:
project_root:PROJECT_ROOTid: numeric id of the entryhard_delete:false(soft-delete; reversible)
For each user memory, call user_forget (agent-memory MCP server) with:
id: numeric id of the entryhard_delete:false
Run all forget calls in parallel.
Step 6: Report
Tell the user how many memories were forgotten and list their summaries. Mention that the deletions are soft (reversible via project_update archive:false or user_update archive:false) unless the user requests permanent removal.
What ships with it
1 file 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.
- 5d ago First seen · 74 lines · 12 tokens per session scan A a9e8e4bf5a11
forget is a skill published in the GitHub repository RashadAnsari/myagents (6 stars, last pushed today), licensed MIT. It adds 12 tokens to every session and 611 once invoked, about $0.0000 per session on Opus 5.5. 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 2026-10-15.
Other skills, from other repositories
memory
Persist and retrieve agent memory across sessions — recall via the three-stage protocol (structure route → semantic search → navigation fallback), read via memoryload, see the wiki structure via memorybrowse, write well-placed pages via memorywrite (including section-level append/rewrite), maintain via memorycurate.…
memory-dream
Curate the workspace memory wiki as its appointed orchestrator. Trigger on a Cloud-scheduled Dream task or a user's direct curation request. Inspect candidates for orphan leaves, near-duplicates, stale pages, remote conflicts and oversized hubs; browse the graph, cluster leaves into INDEX/hub/leaf structure, maintain…
memory-import
Bulk-import an external knowledge base into Prismer memory via the three-layer import pipeline (07 §3.1). Use when the user asks to import/migrate documents, a knowledge base, or notes into workspace memory. Layer 1 lands raw documents (zero LLM, instantly searchable); Layer 2 is YOUR distillation work — you read the…
prismer-obsidian
Read, search, create, and edit notes in the Obsidian vault.
init-workspace-documentation
Skill "init-workspace-documentation" from griddynamics/rosetta, covering agent memory.md, agent memory, preventive rules, what worked and what failed.
memorix-memory
Use when prior workspace context, past decisions, solved bugs, handoff state, or durable project knowledge would help a coding task.