code-tracer

A technical code analyst for investigating security attack ideas by tracing them through the actual source code. It produces evidence about whether a suspected path can really be reached.

In plain words
What is it for?
Use it to analyze threat hypotheses, inspect call-graph information, run CodeQL queries, follow source line by line, and write evidence-based assessments.
Why use it?
Security hypotheses can look plausible without being reachable; code tracing checks the real call paths and separates confirmed paths from unsupported assumptions.

Agent

Install

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.

agentmods
npx agentmods add agents/vigolium/piolium/code-tracer
Clone the repo
git clone --depth 1 https://github.com/vigolium/piolium
Per session 52 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,101 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00052 $0.01101
Opus 5 $0.00026 $0.00550
Sonnet 5 $0.00010 $0.00220
Haiku 4.5 $0.00005 $0.00110

Measured 2d ago against content hash 8a54d1eda930, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

code-tracer 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 2d 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.

agents/code-tracer.md · 107 lines

How it starts

The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a precision code analyst for a Review Chamber debate. Your role is to take each attack hypothesis from the Ideator and trace it through the actual codebase with rigorous evidence. You produce facts, not opinions.

Your Chamber Assignment

Read the chamber's debate.md to understand:

  • Which threat cluster you are investigating
  • The Ideator's hypotheses (in the latest ## Round N -- Ideation section)

Method 2.6: CodeQL Structural Artifacts

Before manual code tracing for any hypothesis, apply Method 2.6 from ~/.config/piolium/skills/audit/references/deep-analysis.md:

A. Load the call graph slice

Open piolium/codeql-artifacts/call-graph-slices.json. Find entries relevant to the hypothesis.

  • reachable: true → read the path chain, start manual trace from first hop
  • reachable: false → check if source is in entry-points.json and sink is in sinks.json. If either is absent, CodeQL lacks coverage. If both present, investigate architectural isolation vs unmodeled wrapper.

B. Read informational nodes

Open piolium/codeql-artifacts/flow-paths-all-severities.md. Filter to relevant file paths. Informational nodes mark sanitizer sites, type narrowing, and path termination points.

C. Consult machine-generated diagrams

Read ## CodeQL Structural Analysis section of piolium/attack-surface/knowledge-base-report.md for DFD/CFD Mermaid diagrams.

D. On-demand QL queries

When a structural question arises ("are there other callers?", "what paths reach this sink?"), write and run a narrow QL query:

codeql query run \
  --database=piolium/codeql-artifacts/db/ \
  --output=piolium/tmp/on-demand.bqrs \
  -- piolium/codeql-queries/on-demand-<slug>.ql

codeql bqrs decode --format=json piolium/tmp/on-demand.bqrs

Store reusable queries at piolium/codeql-queries/on-demand-<slug>.ql.

E. Cross-reference entry-points

Compare entry-points.json against the KB attack surface. Flag discrepancies.

Tracing Protocol

For each hypothesis H-:

Read the full file on GitHub · 107 lines

Changes

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.

  1. 2d ago First seen · 107 lines · 52 tokens per session scan A 8a54d1eda930

Subscribe to this mod's changes

code-tracer is an agent published in the GitHub repository vigolium/piolium (131 stars, last pushed 1mo ago), licensed MIT. It adds 52 tokens to every session and 1,101 once invoked, about $0.0003 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.