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.
npx agentmods add commands/peaky8linders/claude-cortex/hypothesisgit clone --depth 1 https://github.com/Peaky8linders/claude-cortexWhat 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 | $0.00013 | $0.00758 |
| Opus 5 | $0.00006 | $0.00379 |
| Sonnet 5 | $0.00003 | $0.00152 |
| Haiku 4.5 | $0.00001 | $0.00076 |
Grade A, and why
hypothesis 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 3d 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.
How it starts
The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/hypothesis — Manage Learning Hypotheses via Knowledge Graph
You manage hypotheses in the Brainiac knowledge graph. Hypotheses are graph nodes that move through: proposed -> testing -> validated/rejected. Evidence is tracked as causal edges from evidence nodes to the hypothesis node.
System Location
- Engine:
~/.claude/knowledge/brainiac/ - CLI:
cd ~/.claude/knowledge && python -m brainiac <command>
Commands
Parse the user's intent from their message after /hypothesis:
Create a new hypothesis
-
Search existing graph for related hypotheses:
cd ~/.claude/knowledge && python -m brainiac search "TOPIC" -
Add hypothesis as a graph node:
cd ~/.claude/knowledge && python -m brainiac add hypothesis "CLAIM: [testable statement]. EXPECTED: [what we'd observe]. TEST: [how to validate]." -
Also create
~/.claude/knowledge/hypotheses/{kebab-name}.mdwith full detail:--- name: descriptive-name type: hypothesis projects: [relevant-projects] tags: [relevant-tags] created: YYYY-MM-DD updated: YYYY-MM-DD confidence: low status: proposed graph_id: <node ID from step 2> --- ## Claim [Clear, testable statement] ## Expected Outcome [What would we observe if this is true?] ## How to Test [Concrete steps to validate or reject] ## Evidence For <!-- Add dated entries as evidence accumulates --> ## Evidence Against <!-- Add dated entries as evidence accumulates --> ## Verdict Pending — needs more evidence. -
Update
~/.claude/knowledge/hypotheses/INDEX.mdwith the new entry.
Add evidence to an existing hypothesis
- Search for the hypothesis:
cd ~/.claude/knowledge && python -m brainiac search "hypothesis topic" - Update the hypothesis markdown file with dated evidence entry
- Create a causal edge from the evidence source to the hypothesis:
cd ~/.claude/knowledge && python -m brainiac link <evidence_node_id> <hypothesis_node_id> causal - Update confidence (low/medium/high) based on accumulated evidence
- If 3+ data points consistently one way:
- Validated: Set status to
validated. Create a pattern/decision node via/learn. Link hypothesis -> pattern with causal edge. - Rejected: Set status to
rejected. Create an antipattern node via/learn. Link hypothesis -> antipattern with causal edge.
- Validated: Set status to
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.
- 3d ago First seen · 94 lines · 13 tokens per session scan A b11b9389b3db
hypothesis is a command published in the GitHub repository Peaky8linders/claude-cortex (11 stars, last pushed 2mo ago), licensed MIT. It adds 13 tokens to every session and 758 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 2026-08-30.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
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.
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.