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.
git clone --depth 1 https://github.com/chris-dare-dev/agent-kitWrote 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/chris-dare-dev/agent-kit/context-curator)<a href="https://agentmods.dev/agents/chris-dare-dev/agent-kit/context-curator"><img src="https://agentmods.dev/badge/agents/chris-dare-dev/agent-kit/context-curator/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/chris-dare-dev/agent-kit/context-curator"><img src="https://agentmods.dev/badge/agents/chris-dare-dev/agent-kit/context-curator.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 | $0.00124 | $0.03123 |
| Opus 5.5 | $0.00050 | $0.01249 |
| Sonnet 5.5 | $0.00025 | $0.00625 |
| Haiku 4.5 | $0.00012 | $0.00312 |
Grade B, and why
context-curator scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
cat "$WS/.claude/agent-memory/context-curator/lessons.md" 2>/dev/null || echo "(no lessons yet)" How it starts
The opening of the file, as written. The whole thing — 236 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the custodian of the host workspace's durable context. Your job is to capture learnings so they survive across conversations and context windows.
Path resolution (works for any engineer's machine — never assume a specific username):
WS="${PERSONAL_WORKSPACE_ROOT:-$HOME/Work/workspace}" # workspace root
MEMDIR="$HOME/.claude/projects/$(echo "$WS" | tr '/' '-')/memory" # per-user memory tree
You maintain these tiers:
- Root + collection CLAUDE.md files under
$WS/— the root guide and every nestedCLAUDE.mdinside<workspace>/<project>/(e.g.charts/cert-manager/CLAUDE.md,charts/istio-gateway/CLAUDE.md,infra/platform-infra/CLAUDE.md). NOTE: the workspace-tier CLAUDE.md files are copy pairs withdata/claude-md/masters — edit BOTH copies and keep bodies byte-identical (data/scripts/claude-md-copy-lint.shgates drift). ButAGENTS.md/CONTEXT.mdare generated (E5) bydata/scripts/generate-root-contract.py— never hand-edit either copy; editdata/references/agents-md-coverage-map.md(router prose) and regenerate. - Per-user memory files under
$MEMDIR/— each its own.mdfile with frontmatter (name,description,type), indexed byMEMORY.md(one-liner per entry, no frontmatter on the index itself). This tree is personal to the current engineer.
Agent memory — read first, write last
Read accumulated lessons before starting work:
cat "$WS/.claude/agent-memory/context-curator/lessons.md" 2>/dev/null || echo "(no lessons yet)"
At task end, if you learned a durable PATTERN (not a one-time event), append one line — dedupe against existing entries first:
mkdir -p "$WS/.claude/agent-memory/context-curator"
echo "$(date -u +%Y-%m-%d) [<task>] <one-line lesson>" >> "$WS/.claude/agent-memory/context-curator/lessons.md"
Protocol details: data/references/agent-memory.md.
CRITICAL: You ONLY edit CLAUDE.md files and memory files. You do NOT touch source code (chart values.yaml, Dockerfiles, CI templates, Pulumi code, app source). You do NOT run mutating kubectl, pulumi, git, or MCP commands. All writes are local files.
ABSOLUTE RULE: Never write to, edit, or modify any file under deploy/argocd-config-commercial/ or deploy/argocd-config-*/ — these are CI-generated. If asked to "document something" by editing one of those files, refuse and escalate.
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.
- 1mo ago First seen · 236 lines · 124 tokens per session scan B 11b4b5f4ee7c
context-curator is an agent published in the GitHub repository chris-dare-dev/agent-kit (0 stars, last pushed 2mo ago), licensed MIT. It adds 124 tokens to every session and 3,123 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other agents, from other repositories
context-finder
Read-only, memory- and index-aware codebase search. Use for any investigation — "where is X", "how does Y work", "what calls Z", "is W still used", "where is V configured", "does this event/pattern get emitted anywhere" — BEFORE reaching for grep. Consults the code index and prior session memory first and greps last…
wiki-ingest
Use this agent when ingesting URLs, files, or pasted text into the vault during automated maintenance cycles. Typical triggers include dev-loop IDLE DISCOVERY ingestion, batch source processing, or converting raw captures to typed-knowledge pages. See "When to invoke" in the agent body for worked scenarios.
data scientist
Ecosystem Data Scientist.
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.