Heimdall Token Saver Configuration & Diagnostics

Heimdall Token Saver is a drop-in context-window optimizer for AI coding assistants. It compresses the verbose terminal output your agent reads — git diff, pytest, npm install, terraform plan, kubectl, docker — so you spend fewer tokens, stay under your LLM context limit, and get faster, cheaper, more focused responses.

Key Capabilities & CLI Diagnostics

After installation via bdb-dev-optimized-agent-skills, the token-saver command is available system-wide:

• Check Installed Version:

  token-saver version
  

• View Savings Statistics:

  token-saver stats
  token-saver stats --json
  

• Benchmark Command Compression:

  token-saver benchmark 'git diff'
  token-saver benchmark 'pytest' --format json
  token-saver benchmark 'git log -n 20' --dry-run
  

• Check & Apply Updates:

  token-saver update
  

BDB MCP Processors (90-95% Savings on Creative & Media MCPs)

Heimdall includes 6 specialized BDB MCP Processors for creative media and system tools (bdb_td_*, bdb_unreal_*, bdb_after_effects_*, bdb_davinci_*, bdb_resolume_*, memb_mcp):

• 🔮 With Heimdall BDB MCP Processors: You cut token consumption by 90-95% per MCP tool call, allowing your agent to run 10x longer without hitting context limits.

Compression Engine Rules & Guarantees

1. Short Outputs: Commands outputting < 200 characters pass through unchanged.
2. Zero Information Loss: All errors, stack traces, test failure details, and actionable diffs survive intact.
3. Source Code Protection: Pure source code reads (cat *.py, cat *.ts) pass through without compression.
4. Secret Redaction: Environment files (.env) automatically redact secrets before returning to the LLM.

1. Overview

This skill provides domain-specific logic and rules for its respective BDB pipeline component to ensure standardization across multi-agent workflows.

2. When to Use

• Use when specifically requested by the user or triggered by an orchestration agent.
• Use when the current task aligns with the skill's domain.
• Exclude when standard tool execution is sufficient.

3. Core Process

1. Read the provided context and ensure preconditions are met.
2. Run the required script or tool and confirm the state change.
3. Verify exit codes, file modifications, or DB counts to guarantee success before reporting completion.

4. Common Rationalizations

Rationalization	Reality
"The code change was small, so I skipped updating OpenWiki docs."	Every state change must be reflected in the relevant system records.
"The ingest script exited without an error, so the memB index must be updated."	Silent failures happen; explicit verification of the side effect is mandatory.
"I'll let the /startcycle proceed without a defined rollback path."	Proceeding without a rollback path corrupts the workflow integrity and safety.
"I trust the cached agent registry instead of rescanning after a skill change."	Caches stale out quickly; explicit rescans prevent ghost failures.

5. Red Flags

• Bypassing the verification step after a script execution.
• Proceeding to the next pipeline stage without confirming the previous stage's side effects.
• Ignoring domain-specific constraints listed in this skill.

6. Verification

• Verified script exit codes are explicitly checked.
• Confirmed target files or database records reflect the expected change.
• Ensured no silent failures were ignored before reporting success.