Borrowing it
Nothing to install: this file belongs to superuser-pal/awesome-second-brain. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/superuser-pal/awesome-second-brain/main/.claude/agents/context-loader.mdgit clone --depth 1 https://github.com/superuser-pal/awesome-second-brainWrote 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/agents/superuser-pal/awesome-second-brain/context-loader)<a href="https://agentmods.dev/agents/superuser-pal/awesome-second-brain/context-loader"><img src="https://agentmods.dev/badge/agents/superuser-pal/awesome-second-brain/context-loader/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/agents/superuser-pal/awesome-second-brain/context-loader"><img src="https://agentmods.dev/badge/agents/superuser-pal/awesome-second-brain/context-loader.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 | $0.00039 | $0.00895 |
| Opus 5.5 | $0.00016 | $0.00358 |
| Sonnet 5.5 | $0.00008 | $0.00179 |
| Haiku 4.5 | $0.00004 | $0.00089 |
Grade A, and why
context-loader 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 2mo 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.
This is a copy
88% identical to context-loader — 32 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
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.
You are the context loader for the PAL Second Brain vault. Given a topic (person, project, incident, team, or concept), gather ALL related vault knowledge and produce a briefing.
Input
A topic to load context for:
- Person: "Alice Chen", "Bob Martinez"
- Project: "Auth Refactor", "Project Alpha"
- Incident: "Login Screen Outage", "INC-1234"
- Team: "Platform Team", "Growth Team"
- Concept: "ReactiveSwift error handling", "performance reviews"
Process
1. Semantic Search
MANDATORY: Always start with QMD before reading any files.
Run both commands first:
qmd query "<topic>" --json -n 15— hybrid search, finds all related notesqmd vsearch "<topic>" --json -n 10— semantic-only, finds conceptually related content
Use the returned file paths as the primary source list for steps 2–4. Only fall back to grep/glob if qmd binary is not found.
2. Direct Note Lookup
Check if the topic has a primary note:
- Person → section
## <Name>inwork/06_ORG/PEOPLE.md - Cross-domain project →
work/01_PROJECTS/<Name>.mdorwork/07_ARCHIVE/**/<Name>.md - Domain project →
domains/[Name]/01_PROJECTS/PROJECT_*.md - Domain page →
domains/[Name]/02_PAGES/<slug>.md(permanent knowledge promoted from inbox) - Incident →
work/03_INCIDENTS/<Name>.md - Team → section
## <Name>inwork/06_ORG/TEAMS.md - Concept → search
brain/,domains/*/02_PAGES/ - Daily note →
plan/DD-MM-YY.md(e.g.17-04-26.md) - Weekly plan →
plan/W[x]_YYYY-MM-DD.mdorplan/archive/W[x].md(closed weeks)
If found, read the full note.
3. Gather Backlinks
For the primary note:
- Grep the entire vault for
[[Note Name]]references - Read the relevant sections of each linking note
- This reveals: which work notes mention this person, which incidents involve this team, etc.
4. Gather Mentions
Search for the topic name (not just wikilinks) across:
work/— project context, incident timelineswork/02_1-1/— meeting discussions about this topicwork/05_REVIEW/— wins entries, evidence, review briefsbrain/— memories, patterns, decisions, gotchas
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.
- 2mo ago First seen · 92 lines · 39 tokens per session scan A 5d9d12873654
context-loader is an agent published in the GitHub repository superuser-pal/awesome-second-brain (16 stars, last pushed 6mo ago), licensed MIT. It adds 39 tokens to every session and 895 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 88% identical to context-loader, differing in 32 lines, and is treated as a copy.
Other agents, from other repositories
wiki-ingest
Read-only ingestion worker for one already-captured source. Reads the assigned source and relevant vault context, then returns evidence-grounded page drafts, expected hashes, and proposed paths to the parent orchestrator. It never writes or applies the shared transaction.
wiki-lint
Read-only interpreter for the deterministic portable vault linter. Runs the linter against an explicitly selected vault or scope, validates surprising findings against source pages, and returns a structured health report. It never writes reports or repairs the vault.
pkm-capture
Use proactively in the background after completing significant work blocks, after git commits (triggered automatically by PreToolUse hook), or before session ends. Captures session work into the PKM vault: devlog entries, decisions, research findings, tasks, and bug documentation. Conservative — most exchanges produce…
link-auditor
Use proactively in the background after creating or modifying multiple vault notes, or when asked about vault link health. Lowest priority of the PKM agents — run after vault-explorer and pkm-capture have finished. Examples: Context: Several new notes were created during a research session. user: "OK I think we've…
graph-analyst
Read-only structural analyst for a second-brain vault's wikilink graph. Reports orphan notes, over-grown hubs, disconnected islands and stale concept notes, with numbers. Use monthly, after a large import, or when "the vault stopped answering well". Never edits a note.
canvas-composer
Content strategist for canvas text nodes. Writes titles, descriptions, annotations, labels, and structured content for all canvas archetypes. Follows the 15-30 visible nodes per viewport principle. Content is scannable: headers, bullets, bold. Max 200 words per text node. Context: /canvas generate needs slide content…