Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add Syedomershah99/being-human/plugin install being-humanWrote 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/commands/syedomershah99/being-human/learn)<a href="https://agentmods.dev/commands/syedomershah99/being-human/learn"><img src="https://agentmods.dev/badge/commands/syedomershah99/being-human/learn.svg" alt="Measured on agentmods" 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 | $0.00011 | $0.00409 |
| Opus 5 | $0.00005 | $0.00204 |
| Sonnet 5 | $0.00002 | $0.00082 |
| Haiku 4.5 | $0.00001 | $0.00041 |
Grade A, and why
learn scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Build or refresh the voiceprint.
If .being-human/corpus.jsonl does not exist, this is a first run. Do the full setup:
python3 scripts/harvest.py --source claude-history --out .being-human/
python3 scripts/harvest.py --source claude-projects --out .being-human/ --append --contrast
python3 scripts/analyze.py --in .being-human/ --name "$ARGUMENTS"
If it does exist, this is a refresh. Re-harvest with --append to pick up
anything new, then re-analyze. The ## notes section of the existing voiceprint
is preserved automatically — don't recreate it.
Then read .being-human/voiceprint.md and report back, in this order:
- The three or four habits that are most distinctive about how they write. Not the full table — the things that would let someone recognize their writing in a lineup.
- What the contrast pass found. Which words the model has been using with them that they never use. This tends to be the part people find striking, because it's specific to them rather than a list off the internet.
- Anything the numbers look shaky on. Under ~3,000 words, or a corpus that's all short prompts, means the sentence-rhythm figures aren't stable yet. Say so rather than presenting them as settled.
Then ask whether anything is missing — words they've banned, people they're
usually writing for, a habit the numbers wouldn't catch. Write what they say
into ## notes in the voiceprint. That section survives every re-run.
If there's no usable history, don't force it. Switch to interview mode from the skill and ask them the five questions instead.
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.
- 5d ago First seen · 39 lines · 11 tokens per session scan A 58447262d238
learn is a command published in the GitHub repository Syedomershah99/being-human (0 stars, last pushed 23d ago), licensed MIT. It adds 11 tokens to every session and 409 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
constitution
Create or update the project constitution from interactive or provided principle inputs.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.