remember
Skill0 starsChanged 5 months agoMITView on GitHub
Record or view build-time learnings (error fixes, API quirks, config gotchas) that persist across sessions. Proven patterns are injected at session start.
69 other projects use a version of this.
Adopted by
Most recently taken up by
- hydra-db/hydradb-claude-codetheir own version, first seen Nov 8, 2026
- priyansh1210/shirotheir own version, first seen Nov 8, 2026
- jsmastery-pro/jsm-hqtheir own version, first seen Nov 8, 2026
- Yeachan-Heo/oh-my-claudecodetheir own version, first seen Nov 8, 2026
- ArcticFox2029/chamnantheir own version, first seen Nov 5, 2026
- Buddhilive/buddhi-clitheir own version, first seen Nov 1, 2026
Used with
Projects with it also use agent-context-isolation, agentica-infrastructure and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
parcadeiSkillagent-context-isolation
Agent Context Isolation
Also in 3 projects that use this
parcadeiSkillagentica-infrastructure
Reference guide for Agentica multi-agent infrastructure APIs
Also in 3 projects that use this
- +10 more from parcadei
Other versions69 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 69
- github/awesome-copilot★ 41ksame name
- Yeachan-Heo/oh-my-claude-sisyphus★ 41ksame name
- Yeachan-Heo/oh-my-claudecode★ 41ksame name
- langchain-ai/deepagents★ 31ksame name
- parcadei/Continuous-Claude★ 3.9ksame name
- parcadei/Continuous-Claude-v2★ 3.9ksame name
- parcadei/Continuous-Claude-v3★ 3.9ksame name
- zereight/gitlab-mcp★ 2.1ksame name
- H-mmer/pentest-agents★ 815same name
- SparkDevNetwork/Rock★ 701same name
59 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository8 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- browseSkill
- discoverSkill
- onboardSkill
- scaffold-clientSkill
- scaffold-projectSkill
- scaffold-taskSkill
- scaffold-viewerSkill
The file
We split this skill into the rules it gives an agent
12 rules. 0 are common, 6 are distinctive, and 6 are very specific to this project.
0
Common
Most of the 61 edited versions we read keep these.
6
Distinctive
This author's own choices. Worth a look.
6
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 15
If empty or "show" -> View Mode
- Very specific: line 24
Read .outbound-builder-plugin-memory.json from $CLAUDE_PROJECT_DIR.
- Distinctive: line 72
If the category isn't obvious from the text, make your best judgment.
- Distinctive: line 81
Use python3 for deterministic hashing:
- Very specific: line 91
Read .outbound-builder-plugin-memory.json from $CLAUDE_PROJECT_DIR.
- Very specific: line 103
Check if an entry with the same id already exists:
- Very specific: line 141
Write the updated .outbound-builder-plugin-memory.json and confirm:
- Distinctive: line 150
If this entry just became proven (success_count went from 1 to 2), highlight it:
- Distinctive: line 164
Never record routine operations (successful npm install, normal git commands)
- Very specific: line 165
Never record information already documented in imp_doc/
- Distinctive: line 166
Keep titles under 80 characters
- Distinctive: line 167
Keep descriptions and resolutions to 1-2 sentences each
“Common” is measured: kept by at least 6 in 10 of the 61 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Build-Time Memory
You manage the build-time memory system that captures development learnings and makes future building faster.
Mode Detection
Parse $ARGUMENTS:
- If empty or
"show"-> View Mode - Otherwise -> Record Mode (the argument is the learning description)
View Mode
Step 1: Read Memory File
Read .outbound-builder-plugin-memory.json from $CLAUDE_PROJECT_DIR. If it doesn't exist, tell the user:
No build-time memory yet. Learnings are recorded automatically after scaffolding,
or you can record one manually:
/outbound-builder-plugin:remember "Drizzle push needs SSL disabled for Neon"Step 2: Present Summary
Display the memory in this format:
Build-Time Memory: <N> entries (<M> proven patterns)
Proven Patterns (applied at session start):
1. [category] Title -- Resolution
2. ...
Recent Learnings:
- [category] Title (success_count: N)
- ...
Categories: error-fix (<N>), api-quirk (<N>), schema-pattern (<N>),
config-gotcha (<N>), build-pattern (<N>), domain-insight (<N>)Show up to 10 recent learnings (sorted by date descending). Show all proven patterns.
Record Mode
Step 1: Parse the Learning
From $ARGUMENTS, determine:
- category: One of
error-fix,api-quirk,schema-pattern,config-gotcha,build-pattern,domain-insighterror-fix-- A coding error and what fixed itapi-quirk-- Non-obvious API behavior (rate limits, auth, response format)schema-pattern-- Database schema decision or migration insightconfig-gotcha-- Configuration that's easy to get wrongbuild-pattern-- Build/deploy/tooling pattern that works welldomain-insight-- Domain-specific knowledge about the pipeline's use case
- title: Short description (under 80 chars)
- description: What happened (1-2 sentences)
- resolution: What fixed it or what to do (1-2 sentences)
If the category isn't obvious from the text, make your best judgment. If the description is too vague to extract a useful learning, ask the user to be more specific.
Step 2: Generate Entry ID
The ID is mem- followed by an 8-character slug derived from category + title. This enables deduplication -- the same learning discovered twice gets the same ID.
To generate: take the first 8 alphanumeric characters of a lowercase, hyphenated version of category-title. For example:
error-fix+"Drizzle push needs SSL disabled"->mem-errorfix-
Use python3 for deterministic hashing:
import hashlib
slug = hashlib.md5(f"{category}:{title}".lower().encode()).hexdigest()[:8]
entry_id = f"mem-{slug}"Step 3: Read or Create Memory File
Read .outbound-builder-plugin-memory.json from $CLAUDE_PROJECT_DIR. If it doesn't exist, initialize:
{
"version": 1,
"entries": [],
"proven_patterns": []
}Step 4: Dedup and Append
Check if an entry with the same id already exists:
- If yes: Increment
success_countand updatedateto now - If no: Append a new entry:
{
"id": "<generated-id>",
"date": "<ISO timestamp>",
"category": "<category>",
"title": "<title>",
"description": "<description>",
"resolution": "<resolution>",
"context": {
"stage": "manual",
"files": [],
"tech": [],
"domain": null
},
"success_count": 1,
"source": "manual"
}Step 5: Regenerate Proven Patterns
Scan all entries. Any entry with success_count >= 2 becomes a proven pattern. Rebuild the proven_patterns array:
{
"id": "<entry-id>",
"category": "<category>",
"title": "<title>",
"resolution": "<resolution>"
}Step 6: Write and Confirm
Write the updated .outbound-builder-plugin-memory.json and confirm:
Recorded: [category] "title"
-> resolution
(success_count: N, proven: yes/no)If this entry just became proven (success_count went from 1 to 2), highlight it:
This pattern is now PROVEN and will be injected at session start.Rules
- Memory file lives at
$CLAUDE_PROJECT_DIR/.outbound-builder-plugin-memory.json - IDs are deterministic hashes of
category:title-- same learning always gets the same ID - Entries with
success_count >= 2are proven patterns - Proven patterns are injected by the SessionStart hook at every session start
- Never record routine operations (successful npm install, normal git commands)
- Never record information already documented in
imp_doc/ - Keep titles under 80 characters
- Keep descriptions and resolutions to 1-2 sentences each
- The memory file should be committed to the repo (it's project knowledge, not secrets)
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Your trail
Files you open will collect here, so you can find them again.
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Now do this for your own.
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