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DC loki-mode

Multi-agent autonomous startup system for Claude Code. Triggers on "Loki Mode". Orchestrates 100+ specialized agents across engineering, QA, DevOps, security, data/ML, business operations, marketing, HR, and customer success. Takes PRD to fully deployed, revenue-generating product with zero human intervention. Features Task tool for subagent dispatch, parallel code review with 3 specialized reviewers, severity-based issue triage, distributed task queue with dead letter handling, automatic deployment to cloud providers, A/B testing, customer feedback loops, incident response, circuit breakers, and self-healing. Handles rate limits via distributed state checkpoints and auto-resume with exponential backoff. Requires --dangerously-skip-permissions flag.

davila7/claude-code-templates Agent Skills author: davila7 MIT 80 files · 66 scripts body ≈ 6 939 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Multi-agent autonomous startup system for Claude Code.

As a process C 52/100 · Has gaps — References files that are not bundled: references/tool-orchestration.md, references/quality-control.md, references/openai-patterns.md

ProcedurePlaywrightAWSAI and agentstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
D
75/100
safety, quality, tests
Safety 60%
95
Quality 40%
45
Run on models
none yet
Process rating
C
52/100
Has gaps
References files that are not bundled: references/tool-orchestration.md, references/quality-control.md, references/openai-patterns.md
Tools and files w 18
0
Result and completion w 14
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: RA-Skills

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  3. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 1

✓ No critical or high findings

Medium and low: 1
  • medium Dangerous commands cmd-destructive-fs autonomy/run.sh:98
    Destructive filesystem command (wipes root/home/drive) (detector / deny-list definition; string literal in code, not executed)
    BLOCKED_COMMANDS=${LOKI_BLOCKED_COMMANDS:-"rm -rf /,dd if=,mkfs,:(){ :|:& };:"}
    detectorcode literal

Files scanned: 79. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 6939 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: references/tool-orchestration.md
  • warning missing-ref reference to a missing file: references/quality-control.md
  • warning missing-ref reference to a missing file: references/openai-patterns.md
  • warning missing-ref reference to a missing file: references/agent-types.md
  • warning missing-ref reference to a missing file: references/lab-research-patterns.md
  • warning missing-ref reference to a missing file: references/production-patterns.md
  • warning missing-ref reference to a missing file: references/architecture.md
  • warning missing-ref reference to a missing file: references/core-workflow.md
  • warning missing-ref reference to a missing file: references/advanced-patterns.md
  • warning missing-ref reference to a missing file: references/memory-system.md
  • warning missing-ref reference to a missing file: references/task-queue.md
  • warning missing-ref reference to a missing file: references/sdlc-phases.md
  • warning missing-ref reference to a missing file: references/spec-driven-dev.md
  • warning missing-ref reference to a missing file: references/mcp-integration.md
  • warning missing-ref reference to a missing file: references/claude-best-practices.md
  • warning missing-ref reference to a missing file: references/deployment.md
  • warning missing-ref reference to a missing file: references/business-ops.md

Process rating: all ten parameters 52/100

Will not run. References files that are not bundled: references/tool-orchestration.md, references/quality-control.md, references/openai-patterns.md
  • 0Tools and files. 17 referenced file(s) missing: references/tool-orchestration.md, references/quality-control.md, references/openai-patterns.md
  • 0Result and completion. Does not say what the result is
  • 30Running it twice. 8 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 70When it triggers. States when to use, but not when not to
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 6939 tokens
  • 100Steps. 72 steps
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 20 top-level sections: this looks like several domains in one skill

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -5TODO / placeholder text left in the skill
  • +1No license
  • +2Single-language instructions
  • +3Description length 759: enough signal without eating the budget
  • +4Structure: 52 headings
  • +3Step-by-step instructions: 72 items
  • +4Has examples (26 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 45.