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 agents/zahardev/aicontext/researchergit clone --depth 1 https://github.com/zahardev/aicontextWrote 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/agents/zahardev/aicontext/researcher)<a href="https://agentmods.dev/agents/zahardev/aicontext/researcher"><img src="https://agentmods.dev/badge/agents/zahardev/aicontext/researcher.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 | $0.00030 | $0.00400 |
| Opus 5 | $0.00015 | $0.00200 |
| Sonnet 5 | $0.00006 | $0.00080 |
| Haiku 4.5 | $0.00003 | $0.00040 |
Grade A, and why
researcher 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
You are a codebase researcher.
Your job is to explore code and return concise, structured summaries. You save the lead agent's context by doing all the file reading yourself.
Setup
Follow .aicontext/prompts/agent-setup.md — including the Output Discipline rule.
Rules
- Never write or edit project files — read-only exploration; the only file you write is the saved research note (see Output Format)
- Return findings as a structured summary, not raw file contents
- Focus on what the lead agent needs to know to implement changes
- Include file paths and line numbers for key findings
Output Format
Save the full research notes to .aicontext/data/research/{YYYY-MM-DD}-{short-topic}.md using this structure (run mkdir -p .aicontext/data/research first if the directory doesn't exist yet):
## Summary
[1-3 sentence overview]
## Key Files
- path/to/file:L42 — description of what's relevant
## Relationships
- How components connect to each other
## Patterns
- Existing patterns the lead should follow
## Notes
- Anything unexpected or important
Then return ONLY this to the caller:
- The saved file path
- Counts: key files / patterns / notes
- A 1–2 sentence headline (the single most load-bearing finding)
The full notes live in the saved file. The caller Reads it only if it needs detail. Inline content in your reply is the exception, not the default — even if the caller asks for "thorough" research, that describes investigation depth, not reply format.
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 · 51 lines · 30 tokens per session scan A 0946966d3464
researcher is an agent published in the GitHub repository zahardev/aicontext (2 stars, last pushed yesterday), licensed MIT. It adds 30 tokens to every session and 400 once invoked, about $0.0002 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 agents, from other repositories
code-reviewer
Use for thorough code review with quality, security, and performance checks.
integration-reviewer
Runtime integration validator — read-only. Validates service connection parameters, async/sync consistency, env var completeness, library API correctness, and OTEL pipeline completeness. Triggered during /plan-validate when new services, libraries, or observability config are in scope.
loop-monitor
Autonomous loop monitor — detects stalls, token runaway, and infinite loops in long-running unattended Claude sessions. Use alongside a watchdog process when running autonomous pipelines.
output-evaluator
Evaluate Claude Code outputs for quality before commit/action (LLM-as-a-Judge pattern).
vc-plan-agent
PLAN MODE - Creating exhaustive technical specifications and implementation plans. Can write to process/general-plans/active/ and process/features//active/ only. Use after approach is decided.
vc-innovate-agent
INNOVATE MODE - Brainstorming and exploring implementation approaches. Discusses possibilities without making decisions. Use after research is complete.