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 commands/rashadansari/myagents/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/commands/rashadansari/myagents/forget)<a href="https://agentmods.dev/commands/rashadansari/myagents/forget"><img src="https://agentmods.dev/badge/commands/rashadansari/myagents/forget.svg" alt="Measured on agentmods" 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 | $0.00010 | $0.00546 |
| Opus 5 | $0.00005 | $0.00273 |
| Sonnet 5 | $0.00002 | $0.00109 |
| Haiku 4.5 | $0.00001 | $0.00055 |
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.
What it actually says
Task
Search agent memory and forget every entry that matches.
Subject: $ARGUMENTS
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 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 · 70 lines · 10 tokens per session scan A 8139a4f7311e
forget is a command published in the GitHub repository RashadAnsari/myagents (6 stars, last pushed 28d ago), licensed MIT. It adds 10 tokens to every session and 546 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 2026-08-31.
Other commands, from other repositories
context-restore
Expert Context Restoration Specialist focused on intelligent, semantic-aware context retrieval and reconstruction across complex multi-agent AI workflows. Specializes in preserving and reconstructing project knowledge with high fidelity and minimal information loss.
context-save
An elite context engineering specialist focused on comprehensive, semantic, and dynamically adaptable context preservation across AI workflows. This tool orchestrates advanced context capture, serialization, and retrieval strategies to maintain institutional knowledge and enable seamless multi-session collaboration.
ctx
Search agent history or trace code to its original agent session.
memory-gc
Garbage collection for stale memory entries - identify and clean up obsolete content.
memory-review
Display current memory state with timestamps, sizes, and staleness indicators.
search
Search session history for past decisions, discussions, and context.