Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/S3YED/appie-kitnpx agentmods add skills/s3yed/appie-kit/cognify-opsWrote 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/skills/s3yed/appie-kit/cognify-ops)<a href="https://agentmods.dev/skills/s3yed/appie-kit/cognify-ops"><img src="https://agentmods.dev/badge/skills/s3yed/appie-kit/cognify-ops/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/skills/s3yed/appie-kit/cognify-ops"><img src="https://agentmods.dev/badge/skills/s3yed/appie-kit/cognify-ops.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 | $0.00040 | $0.00720 |
| Opus 5 | $0.00020 | $0.00360 |
| Sonnet 5 | $0.00008 | $0.00144 |
| Haiku 4.5 | $0.00004 | $0.00072 |
Grade A, and why
cognify-ops scanned grade A 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 9d 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
r = subprocess.run(["grep", "-v", "^#", "/root/.hermes/.env"], capture_output=True, text=True) How it starts
The opening of the file, as written. The whole thing — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cognify operations (ingestion patterns)
Model selection (CRITICAL)
Default to openai/gpt-4o-mini for entity extraction. DeepSeek V4 Flash hangs on
multi-chunk documents. gpt-4o-mini completes the same document in 25-40s.
Set: COGNIFY_LLM_MODEL=openai/gpt-4o-mini in /root/cognify/.env
Key sourcing
Cognify's .env key goes stale. When extraction fails with "No LLM key", source the
working key from Hermes' env. Use Python to write .env, never shell heredocs —
special chars in API keys cause silent corruption.
import subprocess
r = subprocess.run(["grep", "-v", "^#", "/root/.hermes/.env"], capture_output=True, text=True)
for line in r.stdout.split('\n'):
if 'OPENROUTER_API_KEY' in line and '=' in line:
key = line.split('=', 1)[1].strip().strip('"').strip("'")
with open("/root/cognify/.env", "w") as f:
f.write(f"OPENROUTER_API_KEY={key}\n")
f.write("COGNIFY_LLM_BASE=https://openrouter.ai/api/v1\n")
f.write("COGNIFY_LLM_MODEL=openai/gpt-4o-mini\n")
f.write("COGNIFY_LLM_KEYENV=OPENROUTER_API_KEY\n")
f.write("COGNIFY_BACKEND=local\n")
f.write("COGNIFY_EXTRACT_WORKERS=4\n")
break
Batch ingestion strategy
Combine many small files into batches before ingesting. Use ingest-dir with workers:
cd /root/cognify && set -a && . ./.env && set +a && export COGNIFY_DATA_DIR=/root/.cognify
./.venv/bin/cognify --tenant ramzy ingest-dir /path/to/dir --workers 4
Performance (gpt-4o-mini, 4 workers): ~17K chars/25s, ~35K chars/38s, ~42K chars/42s.
Google Drive transcript extraction
gws drive files export returns 401 even when gws drive files list works.
Workaround: direct Drive API with access token from ~/.config/gws/tokens.json.
Refresh expired tokens: python3 /root/.hermes/scripts/refresh_google_token.py
Typeform response extraction
Contact blocks have nested sub-fields. Recursively parse form definition for ref→label map
before extracting response answers. See references/typeform-extraction.md.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 60 lines · 40 tokens per session scan A 990b5ffd11c9
cognify-ops is a skill published in the GitHub repository S3YED/appie-kit (9 stars, last pushed 17d ago), licensed MIT. It adds 40 tokens to every session and 720 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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