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 skills add dean0x/devflow --skill research-codebasegit clone --depth 1 https://github.com/dean0x/devflowWrote 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/dean0x/devflow/research-codebase)<a href="https://agentmods.dev/skills/dean0x/devflow/research-codebase"><img src="https://agentmods.dev/badge/skills/dean0x/devflow/research-codebase/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/dean0x/devflow/research-codebase"><img src="https://agentmods.dev/badge/skills/dean0x/devflow/research-codebase.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00017 | $0.00852 |
| Opus 5.5 | $0.00007 | $0.00341 |
| Sonnet 5.5 | $0.00003 | $0.00170 |
| Haiku 4.5 | $0.00002 | $0.00085 |
Grade A, and why
research-codebase 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 7d 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 — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codebase Research
Local codebase research for finding patterns, tracing call flows, and mapping module dependencies. No external web access — all evidence comes from the local codebase.
Iron Law
CITE CODE, NOT ASSUMPTIONS
Every claim about the codebase must have file:line evidence. Patterns require 3+ examples to count as patterns. "I believe this is the pattern" without citation is a research failure. If you can't find the evidence, say so — don't invent it.
Trust Tier
trusted — Local code is the authoritative source. All findings carry maximum confidence.
When This Activates
Loaded by Research agent when RESEARCH_TYPE is codebase. Covers:
- Finding existing patterns before implementing new features
- Tracing call chains to understand data flow
- Mapping module boundaries and dependencies
- Identifying conventions used across the codebase
Methodology
Step 1: Define Scope
Before reading anything, define the scope:
- Target area (directory, module, or concept)
- What you are looking for (patterns, functions, conventions, dependencies)
- What files are likely NOT relevant (test fixtures, generated files)
Step 2: Structural Scan
Use Glob and Grep to build a map before reading:
Glob: Find all files matching the area (e.g., src/auth/**/*.ts)
Grep: Search for key terms, function names, type names
Use this to build a candidate file list. Do not read more than 15 files total.
Step 3: Deep Read (Targeted)
Read only the files that the structural scan identified as relevant. Read targeted ranges — not entire files — unless the file is under 50 lines.
Step 4: Pattern Extraction
For each observed pattern:
- Record the first 3 occurrences with file:line
- Describe the pattern in one sentence
- Note any deviations from the pattern
Only declare a pattern after finding 3+ consistent examples.
Step 5: Cross-Reference
Before finalizing findings:
- Check if patterns conflict with each other
- Identify exceptions to patterns you found
- Note if something appears in tests vs production code
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.
- 7d ago Changed · -4 tokens per session 8500a58cfd79
- 1mo ago First seen · 136 lines · 21 tokens per session scan A b49afd52f18b
research-codebase is a skill published in the GitHub repository dean0x/devflow (20 stars, last pushed today), licensed MIT. It adds 17 tokens to every session and 852 once invoked, about $0.0001 per session on Opus 5.5. 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.
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