Research & Analysis🌐universal

trailmark-structural

plugins/trailmark/skills/trailmark-structural/SKILL.md

Runs full Trailmark structural analysis by building a graph, running `preanalysis()`, and reporting hotspots, taint, blast radius, privilege boundaries, attack surface, and version-gated Trailmark 0.4+/0.5+ data such as proxy counts, subgraph edges, type/reference summaries, and entrypoint attributes. Use when vivisect needs detailed structural data for a target. Triggers: structural analysis, blast radius, taint analysis, complexity hotspots, proxy nodes, type references.

Quick Start

Install this SKILL.md

npx skills add https://github.com/trailofbits/skills/tree/main/plugins/trailmark/skills/trailmark-structural
---
name: trailmark-structural
description: "Runs full Trailmark structural analysis by building a graph, running `preanalysis()`, and reporting hotspots, taint, blast radius, privilege boundaries, attack surface, and version-gated Trailmark 0.4+/0.5+ data such as proxy counts, subgraph edges, type/reference summaries, and entrypoint attributes. Use when vivisect needs detailed structural data for a target. Triggers: structural analysis, blast radius, taint analysis, complexity hotspots, proxy nodes, type references."
allowed-tools: Bash Read Grep Glob
---

# Trailmark Structural Analysis

Builds a Trailmark graph and runs `engine.preanalysis()` to compute all
four pre-analysis passes. The core workflow is v0.2-safe; v0.4-only details
are included only after checking method availability, and newer builds
enrich the same output (0.5.0+ adds an `attributes` key to attack-surface
entries and `proxy.external:*` nodes from `.trailmark/links.toml`) without
any workflow change.

## When to Use

- Vivisect Phase 1 needs full structural data (hotspots, taint, blast radius, privilege boundaries)
- Detailed pre-analysis passes for a specific target scope
- Generating complexity and taint data for audit prioritization
- Inspecting proxy/unresolved-call counts, subgraph edges, or type-reference
  summaries when Trailmark 0.4.0+ is installed

## When NOT to Use

- Quick overview only (use `trailmark-summary` instead)
- Ad-hoc code graph queries (use the main `trailmark` skill directly)
- Target is a single small file where structural analysis adds no value

## Rationalizations to Reject

| Rationalization | Why It's Wrong | Required Action |
|-----------------|----------------|-----------------|
| "Summary analysis is enough" | Summary skips taint, blast radius, and privilege boundary data | Run full structural analysis when detailed data is needed |
| "One pass is sufficient" | Passes cross-reference each other — taint without blast radius misses critical nodes | Run all four passes |
| "Tool isn't installed, I'll analyze manually" | Manual analysis misses what tooling catches | Report "trailmark is not installed" and return |
| "Empty pass output means the pass failed" | Some passes produce no data for some codebases (e.g., no privilege boundaries) | Return full output regardless |
| "A v0.4 field is always present" | Users may still have Trailmark 0.2.x installed | Probe with `hasattr()` before querying v0.4-only methods |

## Usage

The target directory is passed via the `args` parameter.

## Execution

**Step 1: Check that trailmark is available.**

```bash
trailmark analyze --help 2>/dev/null || \
  uv run trailmark analyze --help 2>/dev/null
```

If neither command works, report "trailmark is not installed"
and return. Do NOT run `pip install`, `uv pip install`,
`git clone`, or any install command. The user must install
trailmark themselves.

Optionally record the version:

```bash
trailmark --version 2>/dev/null || uv run trailmark --version 2>/dev/null || true
```

Do not fail if this command is missing; use API feature probes below.

**Step 2: Detect languages with Trailmark's parse API.**

```bash
python3 - "{args}" <<'PY'
import json
import sys

try:
    from trailmark.parse import detect_languages  # canonical location since 0.3.x
except ModuleNotFoundError:
    # v0.2.x predates trailmark.parse; the same function lives in query.api
    from trailmark.query.api import detect_languages

print(json.dumps(detect_languages(sys.argv[1])))
PY
```

If the import fails, rerun the same snippet with `uv run --with trailmark python - "{args}"`.
If the result is `[]`, report "Trailmark found no supported languages under
target" and return.

**Step 3: Run the full structural analysis via `QueryEngine`.**

Run this snippet with `python3`. If the import fails, rerun the same snippet
under `uv run --with trailmark python - "{args}"`.

```bash
python3 - "{args}" <<'PY'
import json
import sys

try:
    from trailmark.parse import detect_languages  # canonical location since 0.3.x
except ModuleNotFoundError:
    # v0.2.x predates trailmark.parse; the same function lives in query.api
    from trailmark.query.api import detect_languages

from trailmark.query.api import QueryEngine

target = sys.argv[1]
languages = detect_languages(target)
engine = QueryEngine.from_directory(target, language="auto")
preanalysis = engine.preanalysis()

def summarize_subgraph(name: str, limit: int = 25) -> dict[str, object]:
    nodes = engine.subgraph(name)
    summary = {
        "count": len(nodes),
        "sample_ids": [node["id"] for node in nodes[:limit]],
    }
    if hasattr(engine, "subgraph_edges"):
        summary["edge_count"] = len(engine.subgraph_edges(name))
    return summary

graph = json.loads(engine.to_json())
nodes = graph.get("nodes", {})
proxy_nodes = [
    node_id for node_id, node in nodes.items()
    if node.get("kind") == "proxy" or node.get("origin") == "proxy"
]

payload = {
    "languages": languages,
    "summary": engine.summary(),
    "preanalysis": preanalysis,
    "attack_surface": engine.attack_surface()[:25],
    "hotspots": engine.complexity_hotspots(10)[:25],
    "proxy_nodes": proxy_nodes[:25],
    "subgraphs": {
        name: summarize_subgraph(name)
        for name in engine.subgraph_names()
    },
}

if hasattr(engine, "type_references"):
    payload["type_reference_samples"] = {
        node_id: engine.type_references(node_id)[:10]
        for node_id in list(nodes)[:25]
    }

print(json.dumps(payload, indent=2))
PY
```

**Step 4: Verify the output.**

The output should include:
- `languages`
- `summary`
- `preanalysis`
- `hotspots` (possibly empty)
- `proxy_nodes` (empty on v0.2.x or when there are no unresolved calls; on
  0.5.0+ may include `proxy.external:*` entries declared in
  `.trailmark/links.toml`)
- `subgraphs` with counts and sample IDs

On Trailmark 0.5.0+, `attack_surface` entries may carry an `attributes`
object (e.g. `solidity_visibility`, `solidity_overridden_by`). Pass it
through unchanged — downstream consumers use it to rank entrypoints.

Some subgraphs may have zero nodes for some codebases (this is
normal). Return the full JSON payload regardless.
Repository
7.5kstars
643forks
View on GitHub
Details
DiscoveredOct 14, 2026
Last UpdatedOct 14, 2026
Quality Score
80/100

Related Skills

More research & analysis skills you might like

pr-improver
Research & Analysis
Runs an autonomous review-and-fix improvement loop over the current branch's changes until a PR review comes back clean, scoped mechanically to the directories the branch touched. Reviews are performed by an installed PR-review skill (default: pr-review-toolkit's review-pr). Use to fix review findings on a branch before opening or updating a pull request ('clean up this branch', 'fix this PR until review passes', 'run review-and-fix on my changes'). NOT for a one-time review — run the PR-review skill directly.
🤖claude🌐universal
7.5k
643
View
code-improver
Research & Analysis
Runs an autonomous review-and-fix improvement loop over any code target — a skill, plugin, module, or directory — using a reviewer the user names: any installed skill or agent. Keeps a cross-round findings ledger, escalates when fixes stop converging, and guards scope mechanically. Use when asked to 'improve this code until review passes', 'run an improvement loop with <reviewer>', or to iterate review-and-fix with a specific reviewer. For skills prefer the skill-improver entry; for a branch prefer pr-improver.
🤖claude🌐universal
7.5k
643
View
skill-improver
Research & Analysis
Runs an autonomous review-and-fix improvement loop over a Claude Code skill until a review comes back clean, with a cross-round findings ledger, escalation when fixes stop converging, and a mechanical scope guard. Reviews are performed by the plugin-dev skill-reviewer agent. Use to fix skill quality issues, iteratively refine a skill, or resume a loop after an escalation ('fix my skill', 'improve this skill until it passes review', 'skill improvement loop'). NOT for a one-time review — use the plugin-dev skill-reviewer agent directly.
🤖claude🌐universal
7.5k
643
View
audit-augmentation
Research & Analysis
Augments Trailmark code graphs with external audit findings from SARIF static analysis results, weAudit annotation files, and version-gated Trailmark 0.4.x binary-analysis graph exports. Maps findings to graph nodes by file and line overlap, creates severity-based subgraphs, and enables cross-referencing findings with pre-analysis data (blast radius, taint, etc.). Use when projecting SARIF results onto a code graph, overlaying weAudit annotations, importing binary graph findings, cross-referencing Semgrep, CodeQL, or binary-analysis findings with call graph data, or visualizing audit findings in the context of code structure.
🌐universal
7.5k
643
View