Borrowing it
Nothing to install: this file belongs to moberghr/mtk-agent-toolkit. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/moberghr/mtk-agent-toolkit/main/.claude/skills/incremental-implementation/SKILL.mdgit clone --depth 1 https://github.com/moberghr/mtk-agent-toolkitWrote 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/moberghr/mtk-agent-toolkit/incremental-implementation)<a href="https://agentmods.dev/skills/moberghr/mtk-agent-toolkit/incremental-implementation"><img src="https://agentmods.dev/badge/skills/moberghr/mtk-agent-toolkit/incremental-implementation/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/moberghr/mtk-agent-toolkit/incremental-implementation"><img src="https://agentmods.dev/badge/skills/moberghr/mtk-agent-toolkit/incremental-implementation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 85 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00029 | $0.01527 |
| Opus 5.5 | $0.00012 | $0.00611 |
| Sonnet 5.5 | $0.00006 | $0.00305 |
| Haiku 4.5 | $0.00003 | $0.00153 |
Grade A, and why
incremental-implementation 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 8d 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 — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Incremental Implementation
Overview
Implement in thin slices. Each slice must compile, test, and remain explainable before moving on.
When To Use
- Any approved multi-file implementation
- Refactors that still require verification
- Any task where the cost of late failure is high
When NOT To Use
- Single-file, single-function changes already minimal enough for the fix workflow
Workflow
- Before each batch, re-read the shared references that batch's files match (
context-engineeringstep 3). - Implement only the files listed for the batch, with the smallest correct change.
- Write the tests in the same batch, failing first where the batch adds or fixes behavior (see Batch policy below).
- Run the batch checkpoint using the build and test commands from the active tech stack skill's
## Build & Test Commands. - Capture analyzer output. Write the build output to a log, then feed the log
to the build diagnostics parser. (No
tee /dev/tty: agent shells have no terminal, so it fails.) The parser ships with the plugin; resolve it plugin-first, then the project copy:
Surface any critical analyzer findings immediately — they block the batch just like build failures. Warning-level findings carry forward to the pre-commit review. If the parser resolves nowhere, skip this step.# Example for .NET (adapt command from tech stack skill's Build & Test Commands): PBD="${CLAUDE_PLUGIN_ROOT}/hooks/parse-build-diagnostics.sh"; [ -f "$PBD" ] || PBD=hooks/parse-build-diagnostics.sh mkdir -p .mtk; rc=0; dotnet build > .mtk/build.log 2>&1 || rc=$?; tail -n 30 .mtk/build.log [ -f "$PBD" ] && bash "$PBD" --file .mtk/build.log > .mtk/analyzer-output.json; [ "$rc" -eq 0 ] - Read
.claude/references/pre-commit-review-list.mdif present and fix any violations immediately. - Mark the batch complete in
tasks/todo.md. Record the per-batch gate decision and progress on the workflow artifact in the same shell call as the checkpoint test run —<test cmd> && "$WFA" batch "$MTK_WF_UUID" gate phase_exit_gate pass --reason "batch <id> green" -- set results.batches_completed=<n> -- checkpoint --next "<next batch id: intent>" --verify "<test cmd> => <result>"(checkpointmust be the LAST op; exit 3 means--nextnames a finished unit — fix it and re-runcheckpointalone; on red:|| "$WFA" gate … fail …to trigger remediation). A standalone bookkeeping turn is a wasted turn. Also checkpoint when a PR is opened, before waiting on a usage limit (--wait-until <ISO>), and when the context guard nudges. See.claude/references/orchestration-gates.md. - Churn check: After completing each batch, run
git diff --statand count net lines changed since the last review (intermediate or Phase 4), excluding generated and mechanical files — lockfiles,*.Designer.cs,*.g.cs,*.generated.*, EF migration snapshots,*.min.js/*.min.css, built bundle output (e.g.wwwroot/dist/**). Generated churn is not review load. Thresholds areMTK_CHURN_REVIEW_LINES(default 300) andMTK_CHURN_HALT_LINES(default 500); at rigor HIGH/MAX — the subagent path or the inline-MAX profile — the defaults double to 600/1000, because every batch there is already isolated and drift-checked and a full two-stage review is guaranteed at Phase 4, so the mid-run review is a safety net, not the primary review. If the count exceeds the review threshold, pause and trigger an early review checkpoint:- Run the pre-commit review list if present
- Assess whether the scope is still within the approved manifest
- If the count exceeds the halt threshold without a review, stop and run
compliance-reviewerbefore continuing; the count resets after that review - This catches large unplanned changes mid-implementation rather than at the end
- After all batches, run the full test command from the tech stack and write an explicit behavioral diff.
- Append the
implementsection to the JSON handoff artifact atdocs/specs/<date>-<slug>.json. Schema:.claude/schemas/handoff.schema.json. Required keys:
Be honest about deviations —"implement": { "actual_files": ["..."], // git diff --name-only <base>...HEAD "completed_batches": ["B1","B2"], "deviations": [ { "kind": "extra-file", "detail": "src/Helper.cs", "justification": "needed to unblock B2; spec did not anticipate" } ], "behavioral_diff": "..." }spec-drift-detectionwill diffchange_manifestagainstactual_filesregardless. Runbash scripts/validate-handoff.sh docs/specs/<date>-<slug>.jsonto surface drift before handing off to review.
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.
- 8d ago Changed 2749bd980786
- 16d ago Changed · -7 lines 00ab3540a534
- 1mo ago Changed 27a02afc4374
- 1mo ago Changed 9ee7a67f61f5
- 2mo ago First seen · 102 lines · 29 tokens per session scan A a31af68e0f70
incremental-implementation is a skill published in the GitHub repository moberghr/mtk-agent-toolkit (9 stars, last pushed 8d ago), licensed MIT. It adds 29 tokens to every session and 1,527 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 2026-08-31.
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