Chalk Labs
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Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/epicsagas-context
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: productivity
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/context
What's inside
- Skill name
context- Description
- Working-state snapshot guidance. Restates task/files/decisions in one block so state survives context compaction. Compaction timing is the host's job.
- License
- Apache-2.0
- Instructions
- 28 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Context — Working-State Snapshot Compaction timing belongs to the host (native auto-compaction; the harness already snapshots state on the PreCompact hook). This skill is about WHAT survives, not WHEN to compact. ## Process Before or during compaction, restate the working state in one block: ``` - Working on: [task description] - Files modified: [explicit list] - Status: [what's done, what remains] - Key decisions: [important choices made, with why] - Next step: [what to do after compaction] ``` Keep it terse — this block is what you (and the `resume` hook) reload after compaction. Re-reading large files afterwards costs more than summarizing the key facts beforehand. ## Evidence Required - [ ] Task, files, decisions, and next step all present in the summary block - [ ] Snapshot written by the PreCompact hook (show file name if asked)
From epicsagas/epic-harness, Apache-2.0.
More from epicsagas/epic-harness
- 0.629score
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Systematic vulnerability scan across injection, auth, data exposure, and dependencies — traced by reading code, not grepping for keywords.
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Loop-breaking self-diagnosis.
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Org-level agent team designer via `epic team` CLI (cross-project, append-merge).
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triage
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Adversarial validation of vulnerability findings.
SkillAFreshness: A★ 19Claude Code +9 - 0.629score
threat-model
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Threat modeling and attack surface analysis.
SkillAFreshness: A★ 19Claude Code +9 - 0.629score
benchmark
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Executes Bare-vs-Epic A/B benchmarking, Ring 0 Guard 50 challenge, and full golden set evaluation for epic-harness.
SkillAFreshness: A★ 19Claude Code +9 - 0.629score
document
epicsagas
Documentation generator for public APIs, functions, and modules.
SkillAFreshness: A★ 19Claude Code +9 - 0.626score
debug
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Systematic root-cause isolation for test failures, runtime errors, or unexpected behavior.
SkillAFreshness: A★ 19Claude Code +9 - 0.626score
orchestrate
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Trigger: active multi-agent run.
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reflect
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On-demand human self-assessment of AI usage quality.
SkillAFreshness: A★ 19Claude Code +9 - 0.626score
orbit
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State-persisted autonomous pipeline: spec → go → audit → eval → ship → evolve in one command.
SkillAFreshness: A★ 19Claude Code +9 - 0.626score
go
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Go phase.
SkillAFreshness: A★ 19Claude Code +9
Signals
- Stars
- 19
- Forks
- 5
- Open issues
- 3
- Last commit (this folder)
- Aug 31, 2026 (2 months ago)
- Last release
- Oct 23, 2026 (8 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0
- Repository
- github.com/epicsagas/epic-harness
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Phase 3: Drafting.
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book-fiction
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Fiction craft reference for all subgenres: structure options, scene design, character depth, dialogue, POV and distance, the fiction-specific AI tells, and…
SkillAFreshness: A★ 38Claude Code +9 - 0.638score
book-edit
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Phase 4: Editing.
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Done for you
Rather not set it up yourself?
Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.
See how we build AI agents →Read the case studies
Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
- launches shipped
- 50+
- launches shipped
- media placements
- 500+
- media placements
- founders on every account
- 2
- founders on every account
Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block
Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
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Cite this page
context skill. Agent Mart. https://agentmart.dev/skills/epicsagas-context (last updated 2026-10-24)